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---
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
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