---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- anli
base_model: EleutherAI/gpt-j-6b
model-index:
- name: sft-trl-claim-128
  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. -->

# sft-trl-claim-128

This model is a fine-tuned version of [EleutherAI/gpt-j-6b](https://huggingface.co/EleutherAI/gpt-j-6b) on the anli dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3201

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.4364        | 0.08  | 1000  | 1.8760          |
| 0.9805        | 0.16  | 2000  | 1.2595          |
| 0.6629        | 0.24  | 3000  | 1.2970          |
| 0.4647        | 0.32  | 4000  | 0.9789          |
| 0.4579        | 0.4   | 5000  | 0.8591          |
| 0.383         | 0.48  | 6000  | 0.8866          |
| 0.4915        | 0.56  | 7000  | 0.4281          |
| 0.4139        | 0.64  | 8000  | 0.3946          |
| 0.2563        | 0.72  | 9000  | 0.3653          |
| 0.3179        | 0.8   | 10000 | 0.3528          |
| 0.4199        | 0.88  | 11000 | 0.3602          |
| 0.3877        | 0.96  | 12000 | 0.3457          |
| 0.2332        | 1.04  | 13000 | 0.3882          |
| 0.3817        | 1.11  | 14000 | 0.3604          |
| 0.2734        | 1.19  | 15000 | 0.3613          |
| 0.213         | 1.27  | 16000 | 0.3722          |
| 0.3154        | 1.35  | 17000 | 0.3378          |
| 0.2258        | 1.43  | 18000 | 0.3117          |
| 0.3198        | 1.51  | 19000 | 0.3213          |
| 0.2959        | 1.59  | 20000 | 0.3050          |
| 0.2588        | 1.67  | 21000 | 0.3190          |
| 0.2279        | 1.75  | 22000 | 0.3065          |
| 0.2988        | 1.83  | 23000 | 0.3077          |
| 0.3701        | 1.91  | 24000 | 0.3092          |
| 0.281         | 1.99  | 25000 | 0.3038          |
| 0.1743        | 2.07  | 26000 | 0.3542          |
| 0.1374        | 2.15  | 27000 | 0.3550          |
| 0.1282        | 2.23  | 28000 | 0.3386          |
| 0.1757        | 2.31  | 29000 | 0.3489          |
| 0.1371        | 2.39  | 30000 | 0.3316          |
| 0.1689        | 2.47  | 31000 | 0.3291          |
| 0.1882        | 2.55  | 32000 | 0.3292          |
| 0.1685        | 2.63  | 33000 | 0.3196          |
| 0.1775        | 2.71  | 34000 | 0.3320          |
| 0.1963        | 2.79  | 35000 | 0.3278          |
| 0.1733        | 2.87  | 36000 | 0.3221          |
| 0.1503        | 2.95  | 37000 | 0.3201          |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3