---
library_name: transformers
license: other
base_model: facebook/opt-125m
tags:
- generated_from_trainer
metrics:
- accuracy
- rouge
model-index:
- name: 1e22b46b8eddf5a05a4230f8924cd07c
  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. -->

# 1e22b46b8eddf5a05a4230f8924cd07c

This model is a fine-tuned version of [facebook/opt-125m](https://huggingface.co/facebook/opt-125m) on the nyu-mll/glue [wnli] dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7375
- Data Size: 0.5
- Epoch Runtime: 1.6726
- Accuracy: 0.4375
- F1 Macro: 0.3263
- Rouge1: 0.4375
- Rouge2: 0.0
- Rougel: 0.4375
- Rougelsum: 0.4375

## 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
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Data Size | Epoch Runtime | Accuracy | F1 Macro | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------------:|:--------:|:--------:|:------:|:------:|:------:|:---------:|
| No log        | 0     | 0    | 1.1491          | 0         | 0.8410        | 0.4219   | 0.2967   | 0.4219 | 0.0    | 0.4219 | 0.4219    |
| No log        | 1     | 19   | 1.0610          | 0.0078    | 0.9634        | 0.5469   | 0.3535   | 0.5469 | 0.0    | 0.5469 | 0.5469    |
| No log        | 2     | 38   | 0.7931          | 0.0156    | 0.9641        | 0.5469   | 0.3535   | 0.5469 | 0.0    | 0.5469 | 0.5469    |
| No log        | 3     | 57   | 0.7310          | 0.0312    | 1.0373        | 0.5      | 0.4330   | 0.5    | 0.0    | 0.5    | 0.5       |
| No log        | 4     | 76   | 0.8235          | 0.0625    | 1.0913        | 0.4062   | 0.3552   | 0.4062 | 0.0    | 0.4062 | 0.4062    |
| No log        | 5     | 95   | 0.8062          | 0.125     | 1.0666        | 0.4531   | 0.3347   | 0.4531 | 0.0    | 0.4531 | 0.4531    |
| 0.0946        | 6     | 114  | 0.7590          | 0.25      | 1.2157        | 0.4219   | 0.3660   | 0.4219 | 0.0    | 0.4219 | 0.4219    |
| 0.0946        | 7     | 133  | 0.7375          | 0.5       | 1.6726        | 0.4375   | 0.3263   | 0.4375 | 0.0    | 0.4375 | 0.4375    |


### Framework versions

- Transformers 4.57.0
- Pytorch 2.8.0+cu128
- Datasets 4.3.0
- Tokenizers 0.22.1