File size: 2,776 Bytes
1beac6d |
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 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 |
---
license: apache-2.0
base_model: openai/whisper-base.en
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: whisper-base.en-finetuned-gtzan
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: GTZAN
type: marsyas/gtzan
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.88
---
<!-- 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. -->
# whisper-base.en-finetuned-gtzan
This model is a fine-tuned version of [openai/whisper-base.en](https://huggingface.co/openai/whisper-base.en) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6266
- Accuracy: 0.88
## 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: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 18
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7396 | 1.0 | 75 | 1.6061 | 0.56 |
| 0.8839 | 2.0 | 150 | 0.8286 | 0.77 |
| 0.7631 | 3.0 | 225 | 0.6353 | 0.81 |
| 0.4049 | 4.0 | 300 | 0.5840 | 0.82 |
| 0.3031 | 5.0 | 375 | 0.4069 | 0.88 |
| 0.3031 | 6.0 | 450 | 0.7152 | 0.81 |
| 0.2879 | 7.0 | 525 | 0.7061 | 0.85 |
| 0.0301 | 8.0 | 600 | 0.5691 | 0.89 |
| 0.0311 | 9.0 | 675 | 0.6153 | 0.88 |
| 0.0025 | 10.0 | 750 | 0.5463 | 0.88 |
| 0.0036 | 11.0 | 825 | 0.6017 | 0.89 |
| 0.0016 | 12.0 | 900 | 0.6859 | 0.85 |
| 0.0014 | 13.0 | 975 | 0.5887 | 0.89 |
| 0.0012 | 14.0 | 1050 | 0.6525 | 0.9 |
| 0.0011 | 15.0 | 1125 | 0.6289 | 0.89 |
| 0.0011 | 16.0 | 1200 | 0.6277 | 0.88 |
| 0.001 | 17.0 | 1275 | 0.6274 | 0.88 |
| 0.0611 | 18.0 | 1350 | 0.6266 | 0.88 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3
|