---
license: apache-2.0
base_model: TinyLlama/TinyLlama-1.1B-intermediate-step-1195k-token-2.5T
tags:
- trl
- sft
- generated_from_trainer
datasets:
- generator
model-index:
- name: tinyllama_instruct
  results: []
---

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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/sanjaybasak/tinyllama_instruct_finetuning/runs/e96za0jn)
# tinyllama_instruct

This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-intermediate-step-1195k-token-2.5T](https://huggingface.co/TinyLlama/TinyLlama-1.1B-intermediate-step-1195k-token-2.5T) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8850

## 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: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- 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: 0.1
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.8755        | 0.9981 | 98   | 1.8850          |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.1.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1