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--- |
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base_model: EleutherAI/gpt-neo-125m |
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library_name: peft |
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license: mit |
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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: gpt-neoMedChatbot |
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results: [] |
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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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# gpt-neoMedChatbot |
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This model is a fine-tuned version of [EleutherAI/gpt-neo-125m](https://huggingface.co/EleutherAI/gpt-neo-125m) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.4059 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: constant |
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- lr_scheduler_warmup_ratio: 0.03 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 3.1874 | 0.0709 | 100 | 3.0118 | |
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| 2.8756 | 0.1417 | 200 | 2.8228 | |
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| 2.7134 | 0.2126 | 300 | 2.7358 | |
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| 2.6948 | 0.2835 | 400 | 2.6833 | |
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| 2.6386 | 0.3544 | 500 | 2.6441 | |
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| 2.6525 | 0.4252 | 600 | 2.6150 | |
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| 2.6242 | 0.4961 | 700 | 2.5856 | |
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| 2.6444 | 0.5670 | 800 | 2.5701 | |
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| 2.6007 | 0.6378 | 900 | 2.5540 | |
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| 2.462 | 0.7087 | 1000 | 2.5418 | |
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| 2.5641 | 0.7796 | 1100 | 2.5315 | |
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| 2.4672 | 0.8505 | 1200 | 2.5238 | |
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| 2.5017 | 0.9213 | 1300 | 2.5146 | |
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| 2.6389 | 0.9922 | 1400 | 2.5083 | |
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| 2.4869 | 1.0631 | 1500 | 2.5021 | |
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| 2.5302 | 1.1339 | 1600 | 2.4942 | |
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| 2.497 | 1.2048 | 1700 | 2.4886 | |
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| 2.4965 | 1.2757 | 1800 | 2.4846 | |
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| 2.5535 | 1.3466 | 1900 | 2.4783 | |
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| 2.5747 | 1.4174 | 2000 | 2.4732 | |
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| 2.4534 | 1.4883 | 2100 | 2.4679 | |
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| 2.4909 | 1.5592 | 2200 | 2.4657 | |
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| 2.5192 | 1.6300 | 2300 | 2.4617 | |
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| 2.4271 | 1.7009 | 2400 | 2.4573 | |
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| 2.4855 | 1.7718 | 2500 | 2.4542 | |
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| 2.4599 | 1.8427 | 2600 | 2.4530 | |
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| 2.4482 | 1.9135 | 2700 | 2.4444 | |
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| 2.493 | 1.9844 | 2800 | 2.4446 | |
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| 2.3527 | 2.0553 | 2900 | 2.4414 | |
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| 2.5243 | 2.1262 | 3000 | 2.4376 | |
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| 2.4644 | 2.1970 | 3100 | 2.4330 | |
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| 2.386 | 2.2679 | 3200 | 2.4308 | |
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| 2.3762 | 2.3388 | 3300 | 2.4281 | |
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| 2.3827 | 2.4096 | 3400 | 2.4245 | |
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| 2.3487 | 2.4805 | 3500 | 2.4221 | |
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| 2.4737 | 2.5514 | 3600 | 2.4192 | |
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| 2.4907 | 2.6223 | 3700 | 2.4171 | |
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| 2.3967 | 2.6931 | 3800 | 2.4159 | |
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| 2.4772 | 2.7640 | 3900 | 2.4146 | |
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| 2.4114 | 2.8349 | 4000 | 2.4106 | |
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| 2.4017 | 2.9057 | 4100 | 2.4065 | |
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| 2.3477 | 2.9766 | 4200 | 2.4059 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
