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tsavage68
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IE_M2_1000steps_1e7rate_SFT

Text Generation
Transformers
Safetensors
mistral
trl
sft
Generated from Trainer
conversational
text-generation-inference
Inference Endpoints
Model card Files Community
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  1. README.md +82 -0
  2. config.json +27 -0
  3. final_checkpoint/config.json +27 -0
  4. final_checkpoint/generation_config.json +6 -0
  5. final_checkpoint/model-00001-of-00003.safetensors +3 -0
  6. final_checkpoint/model-00002-of-00003.safetensors +3 -0
  7. final_checkpoint/model-00003-of-00003.safetensors +3 -0
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  9. generation_config.json +6 -0
  10. model-00001-of-00003.safetensors +3 -0
  11. model-00002-of-00003.safetensors +3 -0
  12. model-00003-of-00003.safetensors +3 -0
  13. model.safetensors.index.json +298 -0
  14. special_tokens_map.json +24 -0
  15. tokenizer.json +0 -0
  16. tokenizer_config.json +44 -0
  17. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: mistralai/Mistral-7B-Instruct-v0.2
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+ tags:
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+ - trl
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+ - sft
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+ - generated_from_trainer
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+ model-index:
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+ - name: IE_M2_1000steps_1e7rate_SFT
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # IE_M2_1000steps_1e7rate_SFT
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+
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+ This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.2801
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 1e-07
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+ - train_batch_size: 2
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+ - eval_batch_size: 1
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 4
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_steps: 100
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+ - training_steps: 1000
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | 1.8404 | 0.4 | 50 | 1.8454 |
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+ | 1.6261 | 0.8 | 100 | 1.5552 |
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+ | 1.4351 | 1.2 | 150 | 1.3280 |
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+ | 1.3429 | 1.6 | 200 | 1.3033 |
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+ | 1.3587 | 2.0 | 250 | 1.2943 |
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+ | 1.3562 | 2.4 | 300 | 1.2894 |
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+ | 1.3709 | 2.8 | 350 | 1.2861 |
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+ | 1.2679 | 3.2 | 400 | 1.2843 |
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+ | 1.3609 | 3.6 | 450 | 1.2828 |
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+ | 1.2742 | 4.0 | 500 | 1.2819 |
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+ | 1.3383 | 4.4 | 550 | 1.2812 |
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+ | 1.296 | 4.8 | 600 | 1.2806 |
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+ | 1.3159 | 5.2 | 650 | 1.2804 |
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+ | 1.3007 | 5.6 | 700 | 1.2802 |
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+ | 1.2311 | 6.0 | 750 | 1.2802 |
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+ | 1.2871 | 6.4 | 800 | 1.2802 |
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+ | 1.2652 | 6.8 | 850 | 1.2801 |
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+ | 1.2764 | 7.2 | 900 | 1.2801 |
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+ | 1.2565 | 7.6 | 950 | 1.2801 |
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+ | 1.3073 | 8.0 | 1000 | 1.2801 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.2
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+ - Pytorch 2.0.0+cu117
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+ - Datasets 3.0.0
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+ - Tokenizers 0.19.1
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