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Training with 70/30 Spanish 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_70_30
results: []
---
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# Llama-2-7b-chat-hf-finetune-SWE_70_30
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: 1.3511
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.0759 | 1.0 | 1437 | 0.9557 |
| 0.9237 | 2.0 | 2874 | 0.9524 |
| 0.4326 | 3.0 | 4311 | 1.0528 |
| 0.54 | 4.0 | 5748 | 1.2335 |
| 0.2603 | 5.0 | 7185 | 1.3511 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1