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---
base_model: meta-llama/Meta-Llama-3-8B
library_name: peft
license: llama3
metrics:
- accuracy
- precision
- recall
- f1
tags:
- generated_from_trainer
model-index:
- name: Output_llama2_70-15-15_new
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. -->
# Output_llama2_70-15-15_new
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6310
- Accuracy: 0.6474
- Precision: 0.6760
- Recall: 0.6474
- F1: 0.6376
## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log | 1.0 | 46 | 0.7791 | 0.4808 | 0.2311 | 0.4808 | 0.3122 |
| No log | 2.0 | 92 | 0.7556 | 0.4872 | 0.7519 | 0.4872 | 0.3262 |
| No log | 3.0 | 138 | 0.7071 | 0.5064 | 0.5708 | 0.5064 | 0.4086 |
| No log | 4.0 | 184 | 0.7045 | 0.5 | 0.5549 | 0.5 | 0.3971 |
| No log | 5.0 | 230 | 0.6714 | 0.5705 | 0.6227 | 0.5705 | 0.5340 |
| No log | 6.0 | 276 | 0.6976 | 0.4936 | 0.5303 | 0.4936 | 0.3932 |
| No log | 7.0 | 322 | 0.6453 | 0.6603 | 0.6906 | 0.6603 | 0.6507 |
| No log | 8.0 | 368 | 0.6640 | 0.5769 | 0.6429 | 0.5769 | 0.5354 |
| No log | 9.0 | 414 | 0.6460 | 0.6154 | 0.6643 | 0.6154 | 0.5928 |
| No log | 10.0 | 460 | 0.6310 | 0.6474 | 0.6760 | 0.6474 | 0.6376 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1 |