Hugging Face's logo

vapari
/
distilhubert-finetuned-gtzan

Audio Classification
Transformers
Safetensors
hubert
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
vapari commited on
Commit
3511028
•
1 Parent(s): 7c389e5

End of training

Browse files
Files changed (2) hide show
  1. README.md +15 -27
  2. model.safetensors +1 -1
README.md CHANGED
@@ -23,7 +23,7 @@ model-index:
23
  metrics:
24
  - name: Accuracy
25
  type: accuracy
26
- value: 0.8333333333333334
27
  ---
28
 
29
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -33,8 +33,8 @@ should probably proofread and complete it, then remove this comment. -->
33
 
34
  This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
35
  It achieves the following results on the evaluation set:
36
- - Loss: 0.7729
37
- - Accuracy: 0.8333
38
 
39
  ## Model description
40
 
@@ -53,42 +53,30 @@ More information needed
53
  ### Training hyperparameters
54
 
55
  The following hyperparameters were used during training:
56
- - learning_rate: 5e-05
57
  - train_batch_size: 10
58
  - eval_batch_size: 10
59
  - seed: 42
60
- - gradient_accumulation_steps: 2
61
- - total_train_batch_size: 20
62
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
63
  - lr_scheduler_type: linear
64
  - lr_scheduler_warmup_ratio: 0.1
65
- - num_epochs: 20
66
  - mixed_precision_training: Native AMP
67
 
68
  ### Training results
69
 
70
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
71
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
72
- | 2.188 | 1.0 | 35 | 2.1681 | 0.2692 |
73
- | 1.887 | 2.0 | 70 | 1.8252 | 0.5769 |
74
- | 1.5321 | 3.0 | 105 | 1.4375 | 0.5385 |
75
- | 1.0946 | 4.0 | 140 | 1.2295 | 0.6282 |
76
- | 0.9091 | 5.0 | 175 | 1.0390 | 0.6923 |
77
- | 0.6839 | 6.0 | 210 | 0.9047 | 0.7821 |
78
- | 0.5769 | 7.0 | 245 | 0.8309 | 0.7308 |
79
- | 0.4118 | 8.0 | 280 | 0.9522 | 0.6538 |
80
- | 0.3767 | 9.0 | 315 | 0.8164 | 0.7308 |
81
- | 0.2247 | 10.0 | 350 | 0.6987 | 0.8205 |
82
- | 0.1392 | 11.0 | 385 | 0.7565 | 0.7692 |
83
- | 0.0886 | 12.0 | 420 | 0.7082 | 0.8205 |
84
- | 0.0583 | 13.0 | 455 | 0.7529 | 0.8205 |
85
- | 0.0383 | 14.0 | 490 | 0.7678 | 0.7949 |
86
- | 0.0345 | 15.0 | 525 | 0.7480 | 0.8333 |
87
- | 0.0269 | 16.0 | 560 | 0.7542 | 0.8333 |
88
- | 0.0246 | 17.0 | 595 | 0.7550 | 0.8205 |
89
- | 0.0233 | 18.0 | 630 | 0.7725 | 0.8333 |
90
- | 0.0225 | 19.0 | 665 | 0.7701 | 0.8333 |
91
- | 0.0225 | 20.0 | 700 | 0.7729 | 0.8333 |
92
 
93
 
94
  ### Framework versions
 
23
  metrics:
24
  - name: Accuracy
25
  type: accuracy
26
+ value: 0.7692307692307693
27
  ---
28
 
29
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
33
 
34
  This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
35
  It achieves the following results on the evaluation set:
36
+ - Loss: 1.2256
37
+ - Accuracy: 0.7692
38
 
39
  ## Model description
40
 
 
53
  ### Training hyperparameters
54
 
55
  The following hyperparameters were used during training:
56
+ - learning_rate: 9e-05
57
  - train_batch_size: 10
58
  - eval_batch_size: 10
59
  - seed: 42
 
 
60
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
61
  - lr_scheduler_type: linear
62
  - lr_scheduler_warmup_ratio: 0.1
63
+ - num_epochs: 18
64
  - mixed_precision_training: Native AMP
65
 
66
  ### Training results
67
 
68
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
69
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
70
+ | 1.9893 | 1.0 | 70 | 1.9671 | 0.4615 |
71
+ | 1.1923 | 2.0 | 140 | 1.3634 | 0.5256 |
72
+ | 1.1937 | 3.0 | 210 | 1.0865 | 0.6154 |
73
+ | 0.5684 | 4.0 | 280 | 0.9352 | 0.6795 |
74
+ | 0.4571 | 5.0 | 350 | 0.7889 | 0.7564 |
75
+ | 0.1854 | 6.0 | 420 | 0.8209 | 0.7308 |
76
+ | 0.0688 | 7.0 | 490 | 0.9835 | 0.7692 |
77
+ | 0.087 | 8.0 | 560 | 1.1710 | 0.7179 |
78
+ | 0.0109 | 9.0 | 630 | 1.0900 | 0.7692 |
79
+ | 0.0049 | 10.0 | 700 | 1.2256 | 0.7692 |
 
 
 
 
 
 
 
 
 
 
80
 
81
 
82
  ### Framework versions
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:748efd7cc1f03485c0bfe57a029d43e55c5aa9361d5191d67170563a4ab5c71c
3
  size 94771728
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5a80c1384df2510a8c156bdf93bdb9c7b6a84128c3389d6464ae142e0620136d
3
  size 94771728