---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ser_model_adjusted_2023-03-03___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. -->

# ser_model_adjusted_2023-03-03___2

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: 0.9107
- Accuracy: 0.7443

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.78          | 0.97  | 16   | 1.7021          | 0.2595   |
| 1.5997        | 1.97  | 32   | 1.4990          | 0.4313   |
| 1.5263        | 2.97  | 48   | 1.3821          | 0.4580   |
| 1.3081        | 3.97  | 64   | 1.2632          | 0.5      |
| 1.1996        | 4.97  | 80   | 1.2325          | 0.5115   |
| 1.2048        | 5.97  | 96   | 1.1371          | 0.5611   |
| 1.0209        | 6.97  | 112  | 1.0667          | 0.6145   |
| 1.0388        | 7.97  | 128  | 1.0138          | 0.6679   |
| 0.8895        | 8.97  | 144  | 0.9657          | 0.6947   |
| 0.8569        | 9.97  | 160  | 0.9107          | 0.7443   |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.12.1
- Datasets 2.7.1
- Tokenizers 0.13.2