Training in progress, epoch 0, checkpoint
Browse files- last-checkpoint/README.md +202 -0
- last-checkpoint/adapter_config.json +34 -0
- last-checkpoint/adapter_model.safetensors +3 -0
- last-checkpoint/merges.txt +0 -0
- last-checkpoint/optimizer.pt +3 -0
- last-checkpoint/rng_state.pth +3 -0
- last-checkpoint/scheduler.pt +3 -0
- last-checkpoint/special_tokens_map.json +49 -0
- last-checkpoint/tokenizer.json +0 -0
- last-checkpoint/tokenizer_config.json +170 -0
- last-checkpoint/trainer_state.json +633 -0
- last-checkpoint/training_args.bin +3 -0
- last-checkpoint/vocab.json +0 -0
last-checkpoint/README.md
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---
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base_model: unsloth/SmolLM-360M
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library_name: peft
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---
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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## Model Details
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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- **Developed by:** [More Information Needed]
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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### Model Sources [optional]
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<!-- Provide the basic links for the model. -->
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- **Repository:** [More Information Needed]
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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## Uses
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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### Direct Use
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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[More Information Needed]
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### Downstream Use [optional]
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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[More Information Needed]
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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## How to Get Started with the Model
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Use the code below to get started with the model.
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[More Information Needed]
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## Training Details
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### Training Data
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[More Information Needed]
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### Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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<!-- This should link to a Dataset Card if possible. -->
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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#### Metrics
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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### Results
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[More Information Needed]
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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[More Information Needed]
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## Model Card Contact
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[More Information Needed]
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### Framework versions
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- PEFT 0.13.2
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last-checkpoint/adapter_config.json
ADDED
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "unsloth/SmolLM-360M",
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"bias": "none",
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"fan_in_fan_out": null,
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"inference_mode": true,
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"init_lora_weights": true,
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"layer_replication": null,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 16,
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"lora_dropout": 0.05,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": null,
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"peft_type": "LORA",
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"r": 8,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"down_proj",
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"q_proj",
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"o_proj",
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"k_proj",
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"gate_proj",
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"v_proj",
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"up_proj"
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],
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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"use_rslora": false
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}
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last-checkpoint/adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:130b301554ce6e5ccb1ed449ad9464e91395237d0a95f138537bfe657293749a
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size 17425352
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last-checkpoint/merges.txt
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last-checkpoint/optimizer.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:dfda47560756f4b14b31b3e4b1b6db2c7c6026f00a087799ddb9727a0b33d48e
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size 10252116
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last-checkpoint/rng_state.pth
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:e5b3de583289ed6d30464141f192c4310edef95e4523e0fab1c27a5daba41b00
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size 14244
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last-checkpoint/scheduler.pt
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:705cabf5cbc3a6ab0feb67c77b9b453d59efcc939ce90d310af96e621810f990
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size 1064
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last-checkpoint/special_tokens_map.json
ADDED
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{
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"additional_special_tokens": [
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"<|endoftext|>",
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"<|im_start|>",
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"<|im_end|>",
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"<repo_name>",
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"<reponame>",
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"<file_sep>",
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"<filename>",
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"<gh_stars>",
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"<issue_start>",
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"<issue_comment>",
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"<issue_closed>",
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"<jupyter_start>",
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"<jupyter_text>",
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"<jupyter_code>",
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"<jupyter_output>",
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"<jupyter_script>",
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"<empty_output>"
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],
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"bos_token": {
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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},
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"pad_token": {
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"content": "<empty_output>",
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"unk_token": {
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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}
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}
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last-checkpoint/tokenizer.json
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last-checkpoint/tokenizer_config.json
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|
|
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|
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|
|
|
|
|
1 |
+
{
|
2 |
+
"add_prefix_space": false,
|
3 |
+
"added_tokens_decoder": {
|
4 |
+
"0": {
|
5 |
+
"content": "<|endoftext|>",
|
6 |
+
"lstrip": false,
|
7 |
+
"normalized": false,
|
8 |
+
"rstrip": false,
|
9 |
+
"single_word": false,
|
10 |
+
"special": true
|
11 |
+
},
|
12 |
+
"1": {
|
13 |
+
"content": "<|im_start|>",
|
14 |
+
"lstrip": false,
|
15 |
+
"normalized": false,
|
16 |
+
"rstrip": false,
|
17 |
+
"single_word": false,
|
18 |
+
"special": true
|
19 |
+
},
|
20 |
+
"2": {
|
21 |
+
"content": "<|im_end|>",
|
22 |
+
"lstrip": false,
|
23 |
+
"normalized": false,
|
24 |
+
"rstrip": false,
|
25 |
+
"single_word": false,
|
26 |
+
"special": true
|
27 |
+
},
|
28 |
+
"3": {
|
29 |
+
"content": "<repo_name>",
|
30 |
+
"lstrip": false,
|
31 |
+
"normalized": false,
|
32 |
+
"rstrip": false,
|
33 |
+
"single_word": false,
|
34 |
+
"special": true
|
35 |
+
},
|
36 |
+
"4": {
|
37 |
+
"content": "<reponame>",
|
38 |
+
"lstrip": false,
|
39 |
+
"normalized": false,
|
40 |
+
"rstrip": false,
|
41 |
+
"single_word": false,
|
42 |
+
"special": true
|
43 |
+
},
|
44 |
+
"5": {
|
45 |
+
"content": "<file_sep>",
|
46 |
+
"lstrip": false,
|
47 |
+
"normalized": false,
|
48 |
+
"rstrip": false,
|
49 |
+
"single_word": false,
|
50 |
+
"special": true
|
51 |
+
},
|
52 |
+
"6": {
|
53 |
+
"content": "<filename>",
|
54 |
+
"lstrip": false,
|
55 |
+
"normalized": false,
|
56 |
+
"rstrip": false,
|
57 |
+
"single_word": false,
|
58 |
+
"special": true
|
59 |
+
},
|
60 |
+
"7": {
|
61 |
+
"content": "<gh_stars>",
|
62 |
+
"lstrip": false,
|
63 |
+
"normalized": false,
|
64 |
+
"rstrip": false,
|
65 |
+
"single_word": false,
|
66 |
+
"special": true
|
67 |
+
},
|
68 |
+
"8": {
|
69 |
+
"content": "<issue_start>",
|
70 |
+
"lstrip": false,
|
71 |
+
"normalized": false,
|
72 |
+
"rstrip": false,
|
73 |
+
"single_word": false,
|
74 |
+
"special": true
|
75 |
+
},
|
76 |
+
"9": {
|
77 |
+
"content": "<issue_comment>",
|
78 |
+
"lstrip": false,
|
79 |
+
"normalized": false,
|
80 |
+
"rstrip": false,
|
81 |
+
"single_word": false,
|
82 |
+
"special": true
|
83 |
+
},
|
84 |
+
"10": {
|
85 |
+
"content": "<issue_closed>",
|
86 |
+
"lstrip": false,
|
87 |
+
"normalized": false,
|
88 |
+
"rstrip": false,
|
89 |
+
"single_word": false,
|
90 |
+
"special": true
|
91 |
+
},
|
92 |
+
"11": {
|
93 |
+
"content": "<jupyter_start>",
|
94 |
+
"lstrip": false,
|
95 |
+
"normalized": false,
|
96 |
+
"rstrip": false,
|
97 |
+
"single_word": false,
|
98 |
+
"special": true
|
99 |
+
},
|
100 |
+
"12": {
|
101 |
+
"content": "<jupyter_text>",
|
102 |
+
"lstrip": false,
|
103 |
+
"normalized": false,
|
104 |
+
"rstrip": false,
|
105 |
+
"single_word": false,
|
106 |
+
"special": true
|
107 |
+
},
|
108 |
+
"13": {
|
109 |
+
"content": "<jupyter_code>",
|
110 |
+
"lstrip": false,
|
111 |
+
"normalized": false,
|
112 |
+
"rstrip": false,
|
113 |
+
"single_word": false,
|
114 |
+
"special": true
|
115 |
+
},
|
116 |
+
"14": {
|
117 |
+
"content": "<jupyter_output>",
|
118 |
+
"lstrip": false,
|
119 |
+
"normalized": false,
|
120 |
+
"rstrip": false,
|
121 |
+
"single_word": false,
|
122 |
+
"special": true
|
123 |
+
},
|
124 |
+
"15": {
|
125 |
+
"content": "<jupyter_script>",
|
126 |
+
"lstrip": false,
|
127 |
+
"normalized": false,
|
128 |
+
"rstrip": false,
|
129 |
+
"single_word": false,
|
130 |
+
"special": true
|
131 |
+
},
|
132 |
+
"16": {
|
133 |
+
"content": "<empty_output>",
|
134 |
+
"lstrip": false,
|
135 |
+
"normalized": false,
|
136 |
+
"rstrip": false,
|
137 |
+
"single_word": false,
|
138 |
+
"special": true
|
139 |
+
}
|
140 |
+
},
|
141 |
+
"additional_special_tokens": [
|
142 |
+
"<|endoftext|>",
|
143 |
+
"<|im_start|>",
|
144 |
+
"<|im_end|>",
|
145 |
+
"<repo_name>",
|
146 |
+
"<reponame>",
|
147 |
+
"<file_sep>",
|
148 |
+
"<filename>",
|
149 |
+
"<gh_stars>",
|
150 |
+
"<issue_start>",
|
151 |
+
"<issue_comment>",
|
152 |
+
"<issue_closed>",
|
153 |
+
"<jupyter_start>",
|
154 |
+
"<jupyter_text>",
|
155 |
+
"<jupyter_code>",
|
156 |
+
"<jupyter_output>",
|
157 |
+
"<jupyter_script>",
|
158 |
+
"<empty_output>"
|
159 |
+
],
|
160 |
+
"bos_token": "<|endoftext|>",
|
161 |
+
"chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|>\n\n' }}{% endif %}",
|
162 |
+
"clean_up_tokenization_spaces": false,
|
163 |
+
"eos_token": "<|endoftext|>",
|
164 |
+
"model_max_length": 1000000000000000019884624838656,
|
165 |
+
"pad_token": "<empty_output>",
|
166 |
+
"padding_side": "left",
|
167 |
+
"tokenizer_class": "GPT2Tokenizer",
|
168 |
+
"unk_token": "<|endoftext|>",
|
169 |
+
"vocab_size": 49152
|
170 |
+
}
|
last-checkpoint/trainer_state.json
ADDED
@@ -0,0 +1,633 @@
|
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|
1 |
+
{
|
2 |
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"best_metric": null,
|
3 |
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"best_model_checkpoint": null,
|
4 |
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"epoch": 0.03364030108069467,
|
5 |
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"eval_steps": 100,
|
6 |
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"global_step": 400,
|
7 |
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"is_hyper_param_search": false,
|
8 |
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"is_local_process_zero": true,
|
9 |
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"is_world_process_zero": true,
|
10 |
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"log_history": [
|
11 |
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{
|
12 |
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"epoch": 8.410075270173668e-05,
|
13 |
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"eval_loss": 2.455552101135254,
|
14 |
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"eval_runtime": 138.2596,
|
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"eval_samples_per_second": 36.214,
|
16 |
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"eval_steps_per_second": 18.111,
|
17 |
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"step": 1
|
18 |
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},
|
19 |
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{
|
20 |
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"epoch": 0.0004205037635086834,
|
21 |
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"grad_norm": 0.06288853287696838,
|
22 |
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"learning_rate": 1.6666666666666667e-05,
|
23 |
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"loss": 2.566,
|
24 |
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"step": 5
|
25 |
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},
|
26 |
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{
|
27 |
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"epoch": 0.0008410075270173668,
|
28 |
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"grad_norm": 0.0672573670744896,
|
29 |
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"learning_rate": 3.3333333333333335e-05,
|
30 |
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"loss": 2.4565,
|
31 |
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"step": 10
|
32 |
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},
|
33 |
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{
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