experiments-llama / README.md
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---
base_model: meta-llama/Llama-2-7b-hf
tags:
- generated_from_trainer
datasets:
- pubmed-dataset
model-index:
- name: experiments-llama
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. -->
# experiments-llama
This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on the pubmed-dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7158
## 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: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 2
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.799 | 0.4 | 36 | 1.7739 |
| 1.6351 | 0.8 | 72 | 1.7412 |
| 1.6894 | 1.2 | 108 | 1.7203 |
| 1.7854 | 1.6 | 144 | 1.7165 |
| 1.8052 | 2.0 | 180 | 1.7158 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0