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---
base_model: meta-llama/Llama-2-7b-hf
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: Llama-2-7b-hf-finetuned-mrpc-v0.4
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-hf-finetuned-mrpc-v0.4
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 glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4018
- Accuracy: 0.8431
- F1: 0.8877
## 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: 1.6000000000000003e-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: 16
### Training results
| Training Loss | Epoch | Step | Accuracy | F1 | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:------:|:---------------:|
| No log | 1.0 | 230 | 0.6446 | 0.7695 | 0.6542 |
| No log | 2.0 | 460 | 0.6912 | 0.7968 | 0.5938 |
| 0.6489 | 3.0 | 690 | 0.7230 | 0.8151 | 0.5694 |
| 0.6489 | 4.0 | 920 | 0.7230 | 0.8138 | 0.5503 |
| 0.5299 | 5.0 | 1150 | 0.7402 | 0.8251 | 0.5492 |
| 0.5299 | 6.0 | 1380 | 0.7794 | 0.8432 | 0.4880 |
| 0.4687 | 7.0 | 1610 | 0.8064 | 0.8663 | 0.4559 |
| 0.4687 | 8.0 | 1840 | 0.8186 | 0.875 | 0.4298 |
| 0.374 | 9.0 | 2070 | 0.8284 | 0.8818 | 0.4210 |
| 0.374 | 10.0 | 2300 | 0.8456 | 0.8916 | 0.3953 |
| 0.3096 | 11.0 | 2530 | 0.8431 | 0.8897 | 0.4074 |
| 0.3096 | 12.0 | 2760 | 0.8407 | 0.8862 | 0.4030 |
| 0.3096 | 13.0 | 2990 | 0.3982 | 0.8456 | 0.8904 |
| 0.2799 | 14.0 | 3220 | 0.3873 | 0.8456 | 0.8881 |
| 0.2799 | 15.0 | 3450 | 0.3939 | 0.8529 | 0.8940 |
| 0.2511 | 16.0 | 3680 | 0.4018 | 0.8431 | 0.8877 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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