File size: 2,041 Bytes
6f979b9 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 |
---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: IDAT_grn_aug_275_copy_Wav2Vec
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. -->
# IDAT_grn_aug_275_copy_Wav2Vec
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: 0.1890
- Accuracy: 0.9325
## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6637 | 1.0 | 200 | 0.6039 | 0.7475 |
| 0.5596 | 2.0 | 400 | 0.4814 | 0.7863 |
| 0.5862 | 3.0 | 600 | 0.5135 | 0.72 |
| 0.4844 | 4.0 | 800 | 1.0771 | 0.69 |
| 0.4379 | 5.0 | 1000 | 0.3902 | 0.8263 |
| 0.386 | 6.0 | 1200 | 0.3852 | 0.8263 |
| 0.4857 | 7.0 | 1400 | 0.3531 | 0.8512 |
| 0.3663 | 8.0 | 1600 | 0.3054 | 0.8812 |
| 0.2437 | 9.0 | 1800 | 0.1914 | 0.9437 |
| 0.1738 | 10.0 | 2000 | 0.1890 | 0.9325 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.1.2
- Datasets 2.16.1
- Tokenizers 0.13.3
|