transformers tensorboard safetensors wav2vec2 audio-classification generated_from_trainer base_model:facebook/wav2vec2-base license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wav2vec2-base-finetuned-ic-slurp-no-pretrain
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# wav2vec2-base-finetuned-ic-slurp-no-pretrain

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: 3.1033
- Accuracy: 0.3082

## 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: 5e-05
- train_batch_size: 24
- eval_batch_size: 24
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 96
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 3.8949        | 1.0   | 527   | 3.8954          | 0.0717   |
| 3.8006        | 2.0   | 1055  | 3.8025          | 0.0810   |
| 3.7439        | 3.0   | 1582  | 3.7616          | 0.0821   |
| 3.7199        | 4.0   | 2110  | 3.6873          | 0.0925   |
| 3.6145        | 5.0   | 2637  | 3.6367          | 0.0980   |
| 3.542         | 6.0   | 3165  | 3.5391          | 0.1161   |
| 3.3305        | 7.0   | 3692  | 3.3986          | 0.1528   |
| 3.171         | 8.0   | 4220  | 3.2162          | 0.2022   |
| 2.9197        | 9.0   | 4747  | 3.0826          | 0.2344   |
| 2.6468        | 10.0  | 5275  | 2.9709          | 0.2643   |
| 2.4813        | 11.0  | 5802  | 2.9282          | 0.2880   |
| 2.1928        | 12.0  | 6330  | 2.9192          | 0.2943   |
| 1.9368        | 13.0  | 6857  | 2.9719          | 0.2974   |
| 1.693         | 14.0  | 7385  | 3.0304          | 0.3021   |
| 1.3964        | 15.0  | 7912  | 3.1033          | 0.3082   |
| 1.3051        | 16.0  | 8440  | 3.2700          | 0.2945   |
| 1.0794        | 17.0  | 8967  | 3.4284          | 0.3033   |
| 0.9993        | 18.0  | 9495  | 3.5327          | 0.2998   |
| 0.7641        | 19.0  | 10022 | 3.6907          | 0.2978   |
| 0.68          | 20.0  | 10550 | 3.8579          | 0.2984   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
