---
license: other
tags:
- generated_from_trainer
model-index:
- name: opt-350m-finetuned-v4-seinfeld
  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. -->

# opt-350m-finetuned-v4-seinfeld

This model is a fine-tuned version of [facebook/opt-350m](https://huggingface.co/facebook/opt-350m) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4775

## 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: 0.0005
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.8604        | 0.79  | 8    | 2.7539          |
| 2.8058        | 1.59  | 16   | 2.6860          |
| 2.7427        | 2.4   | 24   | 2.6338          |
| 2.6593        | 3.2   | 32   | 2.5925          |
| 2.5373        | 3.99  | 40   | 2.5601          |
| 2.4923        | 4.79  | 48   | 2.5370          |
| 2.4102        | 5.59  | 56   | 2.5216          |
| 2.3373        | 6.4   | 64   | 2.5049          |
| 2.2341        | 7.2   | 72   | 2.4963          |
| 2.1286        | 7.99  | 80   | 2.4862          |
| 2.0673        | 8.79  | 88   | 2.4908          |
| 1.9938        | 9.59  | 96   | 2.4881          |
| 1.9015        | 10.4  | 104  | 2.4854          |
| 1.8172        | 11.2  | 112  | 2.5058          |
| 1.7113        | 11.99 | 120  | 2.4950          |
| 1.6409        | 12.79 | 128  | 2.5082          |
| 1.5622        | 13.59 | 136  | 2.5172          |
| 1.4724        | 14.4  | 144  | 2.5464          |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.0
- Tokenizers 0.13.2