---
license: mit
tags:
- generated_from_trainer
base_model: EleutherAI/gpt-neo-125m
model-index:
- name: gpt-neo-125m-finetuned-philosopher_rave_20
  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. -->

# gpt-neo-125m-finetuned-philosopher_rave_20

This model is a fine-tuned version of [EleutherAI/gpt-neo-125m](https://huggingface.co/EleutherAI/gpt-neo-125m) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7097

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

20 epochs

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 3e-07
- 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
- num_epochs: 20.0

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 155  | 2.8834          |
| No log        | 2.0   | 310  | 2.8606          |
| No log        | 3.0   | 465  | 2.8407          |
| 2.8695        | 4.0   | 620  | 2.8228          |
| 2.8695        | 5.0   | 775  | 2.8063          |
| 2.8695        | 6.0   | 930  | 2.7911          |
| 2.8122        | 7.0   | 1085 | 2.7772          |
| 2.8122        | 8.0   | 1240 | 2.7650          |
| 2.8122        | 9.0   | 1395 | 2.7544          |
| 2.7613        | 10.0  | 1550 | 2.7454          |
| 2.7613        | 11.0  | 1705 | 2.7378          |
| 2.7613        | 12.0  | 1860 | 2.7313          |
| 2.7397        | 13.0  | 2015 | 2.7258          |
| 2.7397        | 14.0  | 2170 | 2.7211          |
| 2.7397        | 15.0  | 2325 | 2.7173          |
| 2.7397        | 16.0  | 2480 | 2.7143          |
| 2.7214        | 17.0  | 2635 | 2.7121          |
| 2.7214        | 18.0  | 2790 | 2.7106          |
| 2.7214        | 19.0  | 2945 | 2.7098          |
| 2.7104        | 20.0  | 3100 | 2.7097          |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2