---
tags:
- trl
- sft
- generated_from_trainer
datasets:
- generator
model-index:
- name: tinyllama_mole_sft_ultrachat_ep3
  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. -->

# tinyllama_mole_sft_ultrachat_ep3

This model was trained from scratch on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1127

## 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: 16
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 120
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.3007        | 0.09  | 100  | 1.2780          |
| 1.2255        | 0.18  | 200  | 1.2158          |
| 1.192         | 0.26  | 300  | 1.1921          |
| 1.1696        | 0.35  | 400  | 1.1770          |
| 1.1426        | 0.44  | 500  | 1.1666          |
| 1.1628        | 0.53  | 600  | 1.1583          |
| 1.1501        | 0.61  | 700  | 1.1513          |
| 1.137         | 0.7   | 800  | 1.1457          |
| 1.1321        | 0.79  | 900  | 1.1407          |
| 1.1156        | 0.88  | 1000 | 1.1359          |
| 1.1395        | 0.96  | 1100 | 1.1318          |
| 1.0564        | 1.05  | 1200 | 1.1315          |
| 1.0594        | 1.14  | 1300 | 1.1295          |
| 1.0711        | 1.23  | 1400 | 1.1274          |
| 1.0624        | 1.31  | 1500 | 1.1256          |
| 1.0652        | 1.4   | 1600 | 1.1233          |
| 1.0626        | 1.49  | 1700 | 1.1213          |
| 1.0457        | 1.58  | 1800 | 1.1195          |
| 1.0665        | 1.66  | 1900 | 1.1178          |
| 1.07          | 1.75  | 2000 | 1.1158          |
| 1.0567        | 1.84  | 2100 | 1.1141          |
| 1.0304        | 1.93  | 2200 | 1.1127          |
| 1.0132        | 2.01  | 2300 | 1.1170          |
| 1.0203        | 2.1   | 2400 | 1.1170          |
| 1.0088        | 2.19  | 2500 | 1.1168          |
| 1.002         | 2.28  | 2600 | 1.1162          |
| 1.0004        | 2.37  | 2700 | 1.1157          |
| 1.0058        | 2.45  | 2800 | 1.1156          |
| 1.0118        | 2.54  | 2900 | 1.1150          |
| 0.9941        | 2.63  | 3000 | 1.1148          |
| 1.0127        | 2.72  | 3100 | 1.1147          |
| 1.0039        | 2.8   | 3200 | 1.1144          |
| 1.0           | 2.89  | 3300 | 1.1143          |
| 1.0188        | 2.98  | 3400 | 1.1143          |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0