update model card README.md
Browse files
README.md
CHANGED
@@ -4,9 +4,24 @@ tags:
|
|
4 |
- generated_from_trainer
|
5 |
datasets:
|
6 |
- marsyas/gtzan
|
|
|
|
|
7 |
model-index:
|
8 |
- name: distilhubert-finetuned-gtzan
|
9 |
-
results:
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
10 |
---
|
11 |
|
12 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
@@ -16,13 +31,8 @@ should probably proofread and complete it, then remove this comment. -->
|
|
16 |
|
17 |
This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
|
18 |
It achieves the following results on the evaluation set:
|
19 |
-
-
|
20 |
-
-
|
21 |
-
- eval_runtime: 8.0771
|
22 |
-
- eval_samples_per_second: 12.381
|
23 |
-
- eval_steps_per_second: 0.867
|
24 |
-
- epoch: 1.0
|
25 |
-
- step: 57
|
26 |
|
27 |
## Model description
|
28 |
|
@@ -50,6 +60,22 @@ The following hyperparameters were used during training:
|
|
50 |
- lr_scheduler_warmup_ratio: 0.1
|
51 |
- num_epochs: 10
|
52 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
53 |
### Framework versions
|
54 |
|
55 |
- Transformers 4.31.0.dev0
|
|
|
4 |
- generated_from_trainer
|
5 |
datasets:
|
6 |
- marsyas/gtzan
|
7 |
+
metrics:
|
8 |
+
- accuracy
|
9 |
model-index:
|
10 |
- name: distilhubert-finetuned-gtzan
|
11 |
+
results:
|
12 |
+
- task:
|
13 |
+
name: Audio Classification
|
14 |
+
type: audio-classification
|
15 |
+
dataset:
|
16 |
+
name: GTZAN
|
17 |
+
type: marsyas/gtzan
|
18 |
+
config: all
|
19 |
+
split: train
|
20 |
+
args: all
|
21 |
+
metrics:
|
22 |
+
- name: Accuracy
|
23 |
+
type: accuracy
|
24 |
+
value: 0.84
|
25 |
---
|
26 |
|
27 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
|
|
31 |
|
32 |
This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
|
33 |
It achieves the following results on the evaluation set:
|
34 |
+
- Loss: 0.5858
|
35 |
+
- Accuracy: 0.84
|
|
|
|
|
|
|
|
|
|
|
36 |
|
37 |
## Model description
|
38 |
|
|
|
60 |
- lr_scheduler_warmup_ratio: 0.1
|
61 |
- num_epochs: 10
|
62 |
|
63 |
+
### Training results
|
64 |
+
|
65 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
66 |
+
|:-------------:|:-----:|:----:|:---------------:|:--------:|
|
67 |
+
| 2.1135 | 1.0 | 57 | 2.0010 | 0.35 |
|
68 |
+
| 1.534 | 2.0 | 114 | 1.4522 | 0.64 |
|
69 |
+
| 1.1237 | 3.0 | 171 | 1.0933 | 0.73 |
|
70 |
+
| 0.9954 | 4.0 | 228 | 0.9852 | 0.77 |
|
71 |
+
| 0.7052 | 5.0 | 285 | 0.7870 | 0.83 |
|
72 |
+
| 0.6404 | 6.0 | 342 | 0.7186 | 0.79 |
|
73 |
+
| 0.5386 | 7.0 | 399 | 0.6662 | 0.83 |
|
74 |
+
| 0.4455 | 8.0 | 456 | 0.6262 | 0.84 |
|
75 |
+
| 0.387 | 9.0 | 513 | 0.5934 | 0.86 |
|
76 |
+
| 0.3174 | 10.0 | 570 | 0.5858 | 0.84 |
|
77 |
+
|
78 |
+
|
79 |
### Framework versions
|
80 |
|
81 |
- Transformers 4.31.0.dev0
|