|
--- |
|
library_name: transformers |
|
license: mit |
|
base_model: EleutherAI/gpt-neo-1.3B |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: Llama-2-7b-chat-hf |
|
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. --> |
|
|
|
# Llama-2-7b-chat-hf |
|
|
|
This model is a fine-tuned version of [EleutherAI/gpt-neo-1.3B](https://huggingface.co/EleutherAI/gpt-neo-1.3B) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1051 |
|
|
|
## 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: 2e-05 |
|
- train_batch_size: 1 |
|
- eval_batch_size: 1 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 4 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 15 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| No log | 1.0 | 5 | 1.3871 | |
|
| 3.5512 | 2.0 | 10 | 0.1261 | |
|
| 3.5512 | 3.0 | 15 | 0.1115 | |
|
| 0.1406 | 4.0 | 20 | 0.1050 | |
|
| 0.1406 | 5.0 | 25 | 0.1016 | |
|
| 0.0738 | 6.0 | 30 | 0.0973 | |
|
| 0.0738 | 7.0 | 35 | 0.0974 | |
|
| 0.0526 | 8.0 | 40 | 0.0992 | |
|
| 0.0526 | 9.0 | 45 | 0.1030 | |
|
| 0.025 | 10.0 | 50 | 0.1045 | |
|
| 0.025 | 11.0 | 55 | 0.1055 | |
|
| 0.0224 | 12.0 | 60 | 0.1059 | |
|
| 0.0224 | 13.0 | 65 | 0.1054 | |
|
| 0.0134 | 14.0 | 70 | 0.1051 | |
|
| 0.0134 | 15.0 | 75 | 0.1051 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.44.2 |
|
- Pytorch 2.4.0+cu121 |
|
- Datasets 3.0.0 |
|
- Tokenizers 0.19.1 |
|
|
