---
base_model: meta-llama/Llama-2-7b-hf
tags:
- generated_from_trainer
datasets:
- dialogstudio
model-index:
- name: qlora-Llama-2-7b-hf-TweetSumm
  results: []
---

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

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 dialogstudio dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9484

## 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.8058        | 1.0   | 55   | 1.8689          |
| 1.6983        | 2.0   | 110  | 1.8402          |
| 1.5008        | 3.0   | 165  | 1.8654          |
| 1.2814        | 4.0   | 220  | 1.9171          |
| 1.3227        | 5.0   | 275  | 1.9484          |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3