---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: bsc_ai_thesis_torgo_model-1
  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. -->

# bsc_ai_thesis_torgo_model-1

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3445
- Accuracy: 0.8675
- Precision: 0.8670
- Recall: 0.8873

## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|
| 0.6837        | 0.96  | 12   | 0.6315          | 0.695    | 0.6717    | 0.8357 |
| 0.576         | 2.0   | 25   | 0.4980          | 0.7675   | 0.8125    | 0.7324 |
| 0.5089        | 2.96  | 37   | 0.4431          | 0.8125   | 0.8255    | 0.8216 |
| 0.405         | 4.0   | 50   | 0.4718          | 0.8325   | 0.8687    | 0.8075 |
| 0.3436        | 4.96  | 62   | 0.4669          | 0.795    | 0.7331    | 0.9671 |
| 0.318         | 6.0   | 75   | 0.5111          | 0.7225   | 0.6903    | 0.8685 |
| 0.2837        | 6.96  | 87   | 0.5359          | 0.7625   | 0.7783    | 0.7746 |
| 0.2361        | 8.0   | 100  | 0.4633          | 0.805    | 0.8358    | 0.7887 |
| 0.2327        | 8.96  | 112  | 0.3232          | 0.88     | 0.8733    | 0.9061 |
| 0.2036        | 9.6   | 120  | 0.3445          | 0.8675   | 0.8670    | 0.8873 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3