transformers tensorboard safetensors wav2vec2 audio-classification generated_from_trainer base_model:facebook/wav2vec2-base-960h license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/wav2vec2-base-960h
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wav2vec2-base-960h-finetuned-ks
  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. -->

# wav2vec2-base-960h-finetuned-ks

This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6449
- Accuracy: 0.1069

## 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: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 1024
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- lr_scheduler_warmup_steps: 10
- training_steps: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 1    | 2.6379          | 0.0840   |
| 1.3193        | 2.0   | 3    | 2.6377          | 0.0840   |
| 1.1536        | 3.0   | 4    | 2.6374          | 0.0763   |
| 0.8255        | 4.0   | 6    | 2.6377          | 0.0763   |
| 0.8247        | 5.0   | 8    | 2.6390          | 0.0763   |
| 0.8247        | 6.0   | 9    | 2.6387          | 0.0840   |
| 1.1536        | 7.0   | 11   | 2.6415          | 0.0992   |
| 1.3183        | 8.0   | 12   | 2.6408          | 0.0916   |
| 1.3183        | 9.0   | 13   | 2.6402          | 0.0992   |
| 1.3176        | 10.0  | 15   | 2.6414          | 0.0992   |
| 1.1517        | 11.0  | 16   | 2.6419          | 0.0992   |
| 0.823         | 12.0  | 18   | 2.6426          | 0.0992   |
| 0.8222        | 13.0  | 20   | 2.6449          | 0.1069   |
| 0.8222        | 14.0  | 21   | 2.6467          | 0.0992   |
| 1.1534        | 15.0  | 23   | 2.6469          | 0.0916   |
| 1.3186        | 16.0  | 24   | 2.6464          | 0.0840   |
| 1.3186        | 17.0  | 25   | 2.6460          | 0.0840   |
| 1.3143        | 18.0  | 27   | 2.6454          | 0.0916   |
| 1.1482        | 19.0  | 28   | 2.6450          | 0.0840   |
| 0.8229        | 20.0  | 30   | 2.6450          | 0.0840   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
