---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: facebook/wav2vec2-base
model-index:
- name: finetuned_wav2vec2.0-base-on-IEMOCAP_2
  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. -->

# finetuned_wav2vec2.0-base-on-IEMOCAP_2

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1569
- Accuracy: 0.7390

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1881        | 0.99  | 112  | 1.2005          | 0.4768   |
| 1.0121        | 2.0   | 225  | 1.0271          | 0.5619   |
| 0.8569        | 3.0   | 338  | 0.9382          | 0.6018   |
| 0.8679        | 4.0   | 451  | 0.8015          | 0.6947   |
| 0.5643        | 4.99  | 563  | 0.7752          | 0.7046   |
| 0.4579        | 6.0   | 676  | 0.7699          | 0.7400   |
| 0.3993        | 7.0   | 789  | 0.8323          | 0.7102   |
| 0.319         | 8.0   | 902  | 0.7763          | 0.7400   |
| 0.1876        | 8.99  | 1014 | 0.8912          | 0.7334   |
| 0.1888        | 10.0  | 1127 | 0.8836          | 0.7312   |
| 0.1526        | 11.0  | 1240 | 1.0474          | 0.7290   |
| 0.0451        | 12.0  | 1353 | 1.0455          | 0.7434   |
| 0.1281        | 12.99 | 1465 | 1.1207          | 0.7412   |
| 0.0363        | 14.0  | 1578 | 1.1232          | 0.7445   |
| 0.0512        | 14.9  | 1680 | 1.1217          | 0.7412   |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.0
- Datasets 2.12.0
- Tokenizers 0.13.3