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Training with 90/10 english dataset, 5 epochs, 2 Batch Size, reduce_lr_on_plateau
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---
license: llama2
library_name: peft
tags:
- generated_from_trainer
base_model: meta-llama/Llama-2-7b-chat-hf
model-index:
- name: Llama-2-7b-chat-hf-finetune-SWE_90_10_EN
results: []
---
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# Llama-2-7b-chat-hf-finetune-SWE_90_10_EN
This model is a fine-tuned version of [meta-llama/Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9054
## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: reduce_lr_on_plateau
- num_epochs: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.0619 | 0.9995 | 1855 | 1.2754 |
| 0.9448 | 1.9989 | 3710 | 1.2978 |
| 0.3575 | 2.9984 | 5565 | 1.4669 |
| 0.2553 | 3.9978 | 7420 | 1.7785 |
| 0.241 | 4.9973 | 9275 | 1.9054 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1