---
base_model: meta-llama/Llama-2-7b-hf
tags:
- generated_from_trainer
datasets:
- glue
model-index:
- name: Llama-2-7b-hf-finetuned-mrpc
  results: []
library_name: peft
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Llama-2-7b-hf-finetuned-mrpc

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.

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure


The following `bitsandbytes` quantization config was used during training:
- load_in_8bit: True
- load_in_4bit: False
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: fp4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float32
### 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: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1  |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---:|
| No log        | 1.0   | 19   | 0.5879          | 0.75     | 0.8 |


### Framework versions

- PEFT 0.4.0
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3