---
license: apache-2.0
base_model: google/bigbird-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: frame_classification_bigbird
  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. -->

# frame_classification_bigbird

This model is a fine-tuned version of [google/bigbird-roberta-base](https://huggingface.co/google/bigbird-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8803
- Accuracy: 0.8991
- F1: 0.9396
- Precision: 0.9353
- Recall: 0.9440

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Accuracy | F1     | Validation Loss | Precision | Recall |
|:-------------:|:-----:|:-----:|:--------:|:------:|:---------------:|:---------:|:------:|
| 0.6673        | 1.0   | 1288  | 0.9270   | 0.9570 | 0.4955          | 0.9390    | 0.9757 |
| 0.5913        | 2.0   | 2576  | 0.9099   | 0.9477 | 0.6212          | 0.9178    | 0.9795 |
| 0.5858        | 3.0   | 3864  | 0.9270   | 0.9572 | 0.4327          | 0.9343    | 0.9813 |
| 0.5384        | 4.0   | 5152  | 0.9317   | 0.9599 | 0.4998          | 0.9377    | 0.9832 |
| 0.6131        | 5.0   | 6440  | 0.9255   | 0.9561 | 0.5642          | 0.9373    | 0.9757 |
| 0.5834        | 6.0   | 7728  | 0.9239   | 0.9553 | 0.6238          | 0.9340    | 0.9776 |
| 0.5023        | 7.0   | 9016  | 0.9208   | 0.9533 | 0.7194          | 0.9354    | 0.9720 |
| 0.5271        | 8.0   | 10304 | 0.9177   | 0.9516 | 0.7188          | 0.9320    | 0.9720 |
| 0.4755        | 9.0   | 11592 | 0.8618   | 0.9177 | 0.9514          | 0.9351    | 0.9683 |
| 0.4173        | 10.0  | 12880 | 0.8803   | 0.8991 | 0.9396          | 0.9353    | 0.9440 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2