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---
base_model: meta-llama/Llama-2-7b-hf
tags:
- generated_from_trainer
datasets:
- dialogstudio
model-index:
- name: tweet-summarization-llama-2-finetuned
results: []
pipeline_tag: text-generation
---
<!-- 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. -->
# tweet-summarization-llama-2-finetuned
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: 1.9067
## 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: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.0502 | 0.4 | 22 | 2.0521 |
| 1.9097 | 0.8 | 44 | 1.9663 |
| 1.8115 | 1.2 | 66 | 1.9141 |
| 1.8853 | 1.6 | 88 | 1.9079 |
| 1.7765 | 2.0 | 110 | 1.9067 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3