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---
base_model: meta-llama/Llama-2-13b-hf
tags:
- generated_from_trainer
datasets:
- yhavinga/mc4_nl_cleaned
model-index:
- name: tiny-3e-4lr+1152tbs+1ep+0.1wd
  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. -->

# tiny-3e-4lr+1152tbs+1ep+0.1wd

This model is a fine-tuned version of [meta-llama/Llama-2-13b-hf](https://huggingface.co/meta-llama/Llama-2-13b-hf) on the yhavinga/mc4_nl_cleaned micro dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7676

## 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: 0.0003
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- distributed_type: multi-GPU
- num_devices: 16
- gradient_accumulation_steps: 6
- total_train_batch_size: 1152
- total_eval_batch_size: 192
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.8784        | 0.09  | 90   | 1.8820          |
| 1.8344        | 0.19  | 180  | 1.8542          |
| 1.8351        | 0.28  | 270  | 1.8355          |
| 1.8206        | 0.37  | 360  | 1.8212          |
| 1.8021        | 0.47  | 450  | 1.8088          |
| 1.8102        | 0.56  | 540  | 1.7982          |
| 1.7991        | 0.65  | 630  | 1.7890          |
| 1.7788        | 0.74  | 720  | 1.7811          |
| 1.7915        | 0.84  | 810  | 1.7742          |
| 1.7715        | 0.93  | 900  | 1.7676          |


### Framework versions

- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3