Hugging Face's logo

igoeldc
/
distilhubert-finetuned-gtzan

Audio Classification
Transformers
PyTorch
hubert
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
igoeldc commited on
Commit
2714d31
•
1 Parent(s): 0460ea2

End of training

Browse files
Files changed (2) hide show
  1. README.md +14 -16
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
22
  metrics:
23
  - name: Accuracy
24
  type: accuracy
25
- value: 0.81
26
  ---
27
 
28
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
32
 
33
  This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
34
  It achieves the following results on the evaluation set:
35
- - Loss: 0.6443
36
- - Accuracy: 0.81
37
 
38
  ## Model description
39
 
@@ -59,27 +59,25 @@ The following hyperparameters were used during training:
59
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
60
  - lr_scheduler_type: linear
61
  - lr_scheduler_warmup_ratio: 0.1
62
- - num_epochs: 10
63
 
64
  ### Training results
65
 
66
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
67
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
68
- | 1.9572 | 1.0 | 129 | 1.7251 | 0.52 |
69
- | 1.1852 | 2.0 | 258 | 1.1422 | 0.71 |
70
- | 1.1112 | 3.0 | 387 | 0.9251 | 0.72 |
71
- | 0.5134 | 4.0 | 516 | 0.7149 | 0.79 |
72
- | 0.3248 | 5.0 | 645 | 0.7624 | 0.76 |
73
- | 0.332 | 6.0 | 774 | 0.7291 | 0.78 |
74
- | 0.1595 | 7.0 | 903 | 0.6012 | 0.81 |
75
- | 0.1878 | 8.0 | 1032 | 0.5808 | 0.85 |
76
- | 0.0617 | 9.0 | 1161 | 0.6518 | 0.82 |
77
- | 0.0323 | 10.0 | 1290 | 0.6443 | 0.81 |
78
 
79
 
80
  ### Framework versions
81
 
82
  - Transformers 4.32.0.dev0
83
- - Pytorch 2.0.1+cu118
84
- - Datasets 2.14.4
85
  - Tokenizers 0.13.3
 
22
  metrics:
23
  - name: Accuracy
24
  type: accuracy
25
+ value: 0.83
26
  ---
27
 
28
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
32
 
33
  This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
34
  It achieves the following results on the evaluation set:
35
+ - Loss: 0.6209
36
+ - Accuracy: 0.83
37
 
38
  ## Model description
39
 
 
59
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
60
  - lr_scheduler_type: linear
61
  - lr_scheduler_warmup_ratio: 0.1
62
+ - num_epochs: 8
63
 
64
  ### Training results
65
 
66
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
67
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
68
+ | 1.9413 | 1.0 | 129 | 1.7302 | 0.53 |
69
+ | 1.25 | 2.0 | 258 | 1.2193 | 0.67 |
70
+ | 1.1947 | 3.0 | 387 | 0.9074 | 0.73 |
71
+ | 0.6238 | 4.0 | 516 | 0.7667 | 0.77 |
72
+ | 0.4228 | 5.0 | 645 | 0.7407 | 0.76 |
73
+ | 0.3519 | 6.0 | 774 | 0.6948 | 0.8 |
74
+ | 0.2624 | 7.0 | 903 | 0.5938 | 0.85 |
75
+ | 0.3789 | 8.0 | 1032 | 0.6209 | 0.83 |
 
 
76
 
77
 
78
  ### Framework versions
79
 
80
  - Transformers 4.32.0.dev0
81
+ - Pytorch 2.0.0
82
+ - Datasets 2.1.0
83
  - Tokenizers 0.13.3
pytorch_model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:35360ea7c4815c2543711de37089b944a630bfa24b974e09cc4b306134dca537
3
  size 94783376
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d79227c49e1319235be1304fc5d37b782144792b50bdc120f4c99d0cee1c76c6
3
  size 94783376