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distilhubert-finetuned-cry-detector

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  1. README.md +11 -14
  2. checkpoint-170/model.safetensors +1 -1
  3. checkpoint-170/optimizer.pt +1 -1
  4. checkpoint-170/scheduler.pt +1 -1
  5. checkpoint-170/trainer_state.json +19 -19
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  7. checkpoint-256/model.safetensors +1 -1
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  27. checkpoint-426/trainer_state.json +43 -43
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  29. checkpoint-510/config.json +81 -0
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  36. checkpoint-85/model.safetensors +1 -1
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  39. checkpoint-85/trainer_state.json +11 -11
  40. checkpoint-85/training_args.bin +1 -1
  41. model.safetensors +1 -1
  42. runs/Sep06_15-54-59_ubumarcos/events.out.tfevents.1725630900.ubumarcos +3 -0
  43. runs/Sep06_17-32-26_ubumarcos/events.out.tfevents.1725636747.ubumarcos +3 -0
  44. runs/Sep08_21-41-41_ubumarcos/events.out.tfevents.1725824502.ubumarcos +3 -0
  45. runs/Sep08_21-41-41_ubumarcos/events.out.tfevents.1725824503.ubumarcos +3 -0
  46. runs/Sep08_21-42-34_ubumarcos/events.out.tfevents.1725824555.ubumarcos +3 -0
  47. runs/Sep08_21-50-57_ubumarcos/events.out.tfevents.1725825058.ubumarcos +3 -0
  48. training_args.bin +1 -1
README.md CHANGED
@@ -21,11 +21,11 @@ should probably proofread and complete it, then remove this comment. -->
21
 
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  This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on an unknown dataset.
23
  It achieves the following results on the evaluation set:
24
- - Loss: 0.0359
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- - Accuracy: 0.9883
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- - Precision: 0.9883
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- - Recall: 0.9883
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- - F1: 0.9883
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  ## Model description
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@@ -44,7 +44,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 5e-05
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 123
@@ -53,19 +53,16 @@ The following hyperparameters were used during training:
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: cosine
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  - lr_scheduler_warmup_ratio: 0.001
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- - num_epochs: 10
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58
  ### Training results
59
 
60
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
61
  |:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
62
- | No log | 0.9956 | 85 | 0.1341 | 0.9538 | 0.9543 | 0.9538 | 0.9532 |
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- | No log | 1.9912 | 170 | 0.0831 | 0.9700 | 0.9720 | 0.9700 | 0.9703 |
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- | No log | 2.9985 | 256 | 0.0570 | 0.9846 | 0.9847 | 0.9846 | 0.9846 |
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- | No log | 3.9941 | 341 | 0.0340 | 0.9897 | 0.9898 | 0.9897 | 0.9898 |
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- | No log | 4.9898 | 426 | 0.0460 | 0.9875 | 0.9879 | 0.9875 | 0.9876 |
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- | 0.0707 | 5.9971 | 512 | 0.0431 | 0.9897 | 0.9899 | 0.9897 | 0.9898 |
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- | 0.0707 | 6.9927 | 597 | 0.0359 | 0.9883 | 0.9883 | 0.9883 | 0.9883 |
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70
 
71
  ### Framework versions
 
21
 
22
  This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on an unknown dataset.
23
  It achieves the following results on the evaluation set:
24
+ - Loss: 0.0625
25
+ - Accuracy: 0.9824
26
+ - Precision: 0.9825
27
+ - Recall: 0.9824
28
+ - F1: 0.9824
29
 
30
  ## Model description
31
 
 
44
  ### Training hyperparameters
45
 
46
  The following hyperparameters were used during training:
47
+ - learning_rate: 3e-05
48
  - train_batch_size: 8
49
  - eval_batch_size: 8
50
  - seed: 123
 
53
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
54
  - lr_scheduler_type: cosine
55
  - lr_scheduler_warmup_ratio: 0.001
56
+ - num_epochs: 4
57
 
58
  ### Training results
59
 
60
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
61
  |:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
62
+ | No log | 0.9956 | 85 | 0.1378 | 0.9546 | 0.9543 | 0.9546 | 0.9544 |
63
+ | No log | 1.9912 | 170 | 0.0802 | 0.9714 | 0.9713 | 0.9714 | 0.9714 |
64
+ | No log | 2.9985 | 256 | 0.0682 | 0.9780 | 0.9783 | 0.9780 | 0.9781 |
65
+ | No log | 3.9824 | 340 | 0.0625 | 0.9824 | 0.9825 | 0.9824 | 0.9824 |
 
 
 
66
 
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  ### Framework versions
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