File size: 2,043 Bytes
2842da5 |
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_red_aug_290_novel_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_red_aug_290_novel_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: 0.5251
- Accuracy: 0.7468
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.595 | 0.99 | 40 | 0.6560 | 0.6013 |
| 0.4853 | 1.99 | 80 | 0.5651 | 0.7342 |
| 0.46 | 2.98 | 120 | 0.5168 | 0.7468 |
| 0.4401 | 4.0 | 161 | 0.5230 | 0.7848 |
| 0.3787 | 4.99 | 201 | 0.6051 | 0.7468 |
| 0.465 | 5.99 | 241 | 0.7267 | 0.6646 |
| 0.4037 | 6.98 | 281 | 0.4611 | 0.7911 |
| 0.4508 | 8.0 | 322 | 0.6489 | 0.7468 |
| 0.4427 | 8.99 | 362 | 0.4774 | 0.7848 |
| 0.399 | 9.94 | 400 | 0.5251 | 0.7468 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.1.2
- Datasets 2.16.1
- Tokenizers 0.13.3
|