README.md

---
library_name: transformers
license: apache-2.0
base_model: superb/wav2vec2-base-superb-sid
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: transcribe-monkey
  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. -->

# transcribe-monkey

This model is a fine-tuned version of [superb/wav2vec2-base-superb-sid](https://huggingface.co/superb/wav2vec2-base-superb-sid) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2787
- Accuracy: 0.9677

## 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
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1226        | 1.0   | 212  | 0.4222          | 0.9516   |
| 0.2144        | 2.0   | 424  | 0.2416          | 0.9516   |
| 0.0888        | 3.0   | 636  | 0.2240          | 0.9677   |
| 0.0004        | 4.0   | 848  | 0.3074          | 0.9677   |
| 0.0204        | 5.0   | 1060 | 0.2787          | 0.9677   |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.3.0
- Datasets 3.1.0
- Tokenizers 0.20.3