NicholasCorrado
commited on
Commit
•
328542f
1
Parent(s):
a0b90b2
Model save
Browse files- README.md +17 -16
- all_results.json +6 -6
- model-00001-of-00003.safetensors +1 -1
- model-00002-of-00003.safetensors +1 -1
- model-00003-of-00003.safetensors +1 -1
- train_results.json +6 -6
- trainer_state.json +1521 -16
README.md
CHANGED
@@ -3,15 +3,10 @@ library_name: transformers
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license: apache-2.0
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base_model: alignment-handbook/zephyr-7b-sft-full
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tags:
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- alignment-handbook
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- trl
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- dpo
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- generated_from_trainer
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- trl
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- dpo
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- generated_from_trainer
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datasets:
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- data/rlced_conifer
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model-index:
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- name: rlced-conifer-zephyr-7b-dpo-2e
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results: []
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@@ -22,17 +17,17 @@ should probably proofread and complete it, then remove this comment. -->
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# rlced-conifer-zephyr-7b-dpo-2e
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This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-full](https://huggingface.co/alignment-handbook/zephyr-7b-sft-full) on
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Rewards/chosen:
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- Rewards/rejected:
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- Rewards/accuracies: 0.
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- Rewards/margins:
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- Logps/rejected: -
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- Logps/chosen: -
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- Logits/rejected:
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- Logits/chosen: -
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## Model description
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### Training results
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### Framework versions
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license: apache-2.0
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base_model: alignment-handbook/zephyr-7b-sft-full
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tags:
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- trl
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- dpo
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+
- alignment-handbook
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- generated_from_trainer
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model-index:
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- name: rlced-conifer-zephyr-7b-dpo-2e
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results: []
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# rlced-conifer-zephyr-7b-dpo-2e
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This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-full](https://huggingface.co/alignment-handbook/zephyr-7b-sft-full) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1578
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- Rewards/chosen: -8.8688
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- Rewards/rejected: -21.7065
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- Rewards/accuracies: 0.9203
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- Rewards/margins: 12.8376
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- Logps/rejected: -2616.5852
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- Logps/chosen: -1310.2896
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- Logits/rejected: 3.0165
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- Logits/chosen: -0.1724
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## Model description
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
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|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
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| 0.1586 | 0.4982 | 240 | 0.1689 | -2.6868 | -8.8615 | 0.9252 | 6.1746 | -1332.0890 | -692.0928 | 1.5975 | -0.1975 |
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| 0.1408 | 0.9964 | 480 | 0.1482 | -6.5979 | -15.9265 | 0.9326 | 9.3286 | -2038.5934 | -1083.2030 | 3.3424 | 0.5015 |
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| 0.0852 | 1.4946 | 720 | 0.1644 | -10.0141 | -23.7065 | 0.9228 | 13.6924 | -2816.5886 | -1424.8193 | 3.4873 | 0.0636 |
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| 0.0743 | 1.9927 | 960 | 0.1578 | -8.8688 | -21.7065 | 0.9203 | 12.8376 | -2616.5852 | -1310.2896 | 3.0165 | -0.1724 |
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### Framework versions
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all_results.json
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@@ -1,5 +1,5 @@
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{
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-
"epoch":
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"eval_logits/chosen": -2.8249309062957764,
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"eval_logits/rejected": -2.6878879070281982,
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"eval_logps/chosen": -401.2567138671875,
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"eval_samples_per_second": 17.099,
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"eval_steps_per_second": 0.342,
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"total_flos": 0.0,
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"train_loss": 0.
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"train_runtime":
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"train_samples":
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"train_samples_per_second":
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"train_steps_per_second": 0.
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}
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{
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"epoch": 1.996886351842242,
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"eval_logits/chosen": -2.8249309062957764,
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"eval_logits/rejected": -2.6878879070281982,
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"eval_logps/chosen": -401.2567138671875,
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"eval_samples_per_second": 17.099,
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"eval_steps_per_second": 0.342,
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"total_flos": 0.0,
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+
"train_loss": 0.1585804910288655,
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"train_runtime": 28225.2793,
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"train_samples": 123309,
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"train_samples_per_second": 8.737,
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"train_steps_per_second": 0.034
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}
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model-00001-of-00003.safetensors
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size 4943162336
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model-00002-of-00003.safetensors
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size 4999819336
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model-00003-of-00003.safetensors
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train_results.json
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{
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"total_flos": 0.0,
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"train_runtime":
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{
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"train_loss": 0.1585804910288655,
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"train_runtime": 28225.2793,
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"train_samples": 123309,
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"train_samples_per_second": 8.737,
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"train_steps_per_second": 0.034
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}
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trainer_state.json
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{
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"best_metric": null,
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"best_model_checkpoint": null,
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-
"epoch":
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"eval_steps": 240,
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-
"global_step":
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"is_hyper_param_search": false,
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"is_local_process_zero": true,
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"is_world_process_zero": true,
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"log_history": [
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{
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"epoch":
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"logits/
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"logps/
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"rewards/accuracies": 0.0,
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"rewards/chosen": 0.0,
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"rewards/margins": 0.0,
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{
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"epoch":
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