---
library_name: transformers
license: llama3.1
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: l3.1-8b-inst-fft-induction-barc-heavy-200k-lr1e-5-ep2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# l3.1-8b-inst-fft-induction-barc-heavy-200k-lr1e-5-ep2

This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co./meta-llama/Meta-Llama-3.1-8B-Instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2765

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 128
- total_eval_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.2944        | 1.0   | 1478 | 0.2865          |
| 0.2388        | 2.0   | 2956 | 0.2765          |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.4.1+cu124
- Datasets 3.0.2
- Tokenizers 0.19.1