llama3-2M-MedEV / README.md
Angelectronic's picture
Update README.md
d653cd2 verified
---
license: apache-2.0
library_name: peft
tags:
- trl
- sft
- unsloth
- generated_from_trainer
base_model: unsloth/llama-3-8b-Instruct-bnb-4bit
model-index:
- name: llama3-2M-MedEV
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. -->
# llama3-2M-MedEV
This model is a fine-tuned version of [unsloth/llama-3-8b-Instruct-bnb-4bit](https://huggingface.co./unsloth/llama-3-8b-Instruct-bnb-4bit) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4249
- Bleu: 47.7973
## 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: 0.0002
- train_batch_size: 32
- eval_batch_size: 16
- seed: 3407
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 5
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.534 | 0.1200 | 320 | 1.4902 |
| 1.3171 | 0.2399 | 640 | 1.4705 |
| 1.29 | 0.3599 | 960 | 1.4644 |
| 1.2699 | 0.4798 | 1280 | 1.4287 |
| 1.2567 | 0.5998 | 1600 | 1.4576 |
| 1.2448 | 0.7197 | 1920 | 1.4196 |
| 1.2353 | 0.8397 | 2240 | 1.4249 |
| 1.2274 | 0.9596 | 2560 | 1.4172 |
| 1.1635 | 1.0796 | 2880 | 1.4180 |
| 1.1337 | 1.1995 | 3200 | 1.4219 |
| 1.1346 | 1.3195 | 3520 | 1.3954 |
| 1.131 | 1.4394 | 3840 | 1.3714 |
| 1.1325 | 1.5594 | 4160 | 1.3923 |
| 1.1269 | 1.6793 | 4480 | 1.4118 |
| 1.1221 | 1.7993 | 4800 | 1.4251 |
| 1.1226 | 1.9192 | 5120 | 1.3970 |
| 1.0898 | 2.0392 | 5440 | 1.4198 |
| 1.0372 | 2.1591 | 5760 | 1.4310 |
| 1.0325 | 2.2791 | 6080 | 1.4209 |
| 1.0334 | 2.3990 | 6400 | 1.4205 |
| 1.0328 | 2.5190 | 6720 | 1.4306 |
| 1.0303 | 2.6389 | 7040 | 1.4222 |
| 1.0283 | 2.7589 | 7360 | 1.4266 |
| 1.0273 | 2.8788 | 7680 | 1.4251 |
| 1.0295 | 2.9988 | 8000 | 1.4249 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.40.2
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1