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