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tsavage68
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Na_M2_1000steps_1e6rate_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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End of training

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Files changed (17) hide show
  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: Na_M2_1000steps_1e6rate_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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+ # Na_M2_1000steps_1e6rate_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: 0.1550
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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-06
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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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+ | 0.349 | 0.2667 | 50 | 0.3425 |
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+ | 0.2797 | 0.5333 | 100 | 0.2671 |
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+ | 0.1882 | 0.8 | 150 | 0.1831 |
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+ | 0.1593 | 1.0667 | 200 | 0.1748 |
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+ | 0.1609 | 1.3333 | 250 | 0.1586 |
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+ | 0.1544 | 1.6 | 300 | 0.1575 |
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+ | 0.1558 | 1.8667 | 350 | 0.1564 |
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+ | 0.1524 | 2.1333 | 400 | 0.1574 |
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+ | 0.1527 | 2.4 | 450 | 0.1568 |
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+ | 0.1564 | 2.6667 | 500 | 0.1554 |
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+ | 0.1523 | 2.9333 | 550 | 0.1563 |
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+ | 0.1519 | 3.2 | 600 | 0.1558 |
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+ | 0.1532 | 3.4667 | 650 | 0.1555 |
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+ | 0.1508 | 3.7333 | 700 | 0.1549 |
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+ | 0.1518 | 4.0 | 750 | 0.1550 |
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+ | 0.1507 | 4.2667 | 800 | 0.1551 |
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+ | 0.1501 | 4.5333 | 850 | 0.1550 |
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+ | 0.1477 | 4.8 | 900 | 0.1549 |
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+ | 0.1464 | 5.0667 | 950 | 0.1550 |
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+ | 0.1488 | 5.3333 | 1000 | 0.1550 |
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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 2.4.0+cu121
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+ - Datasets 2.21.0
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+ - Tokenizers 0.19.1
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