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Adzka/reward-model-distilbert-indo

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Files changed (21) hide show
  1. README.md +11 -12
  2. emissions.csv +6 -1
  3. model.safetensors +1 -1
  4. runs/Jul02_02-10-09_DESKTOP-HH0RPGN/events.out.tfevents.1719861015.DESKTOP-HH0RPGN.3516.0 +3 -0
  5. runs/Jul02_02-10-09_DESKTOP-HH0RPGN/events.out.tfevents.1719861946.DESKTOP-HH0RPGN.3516.1 +3 -0
  6. runs/Jul02_02-25-47_DESKTOP-HH0RPGN/events.out.tfevents.1719861953.DESKTOP-HH0RPGN.3516.2 +3 -0
  7. runs/Jul02_02-25-47_DESKTOP-HH0RPGN/events.out.tfevents.1719862349.DESKTOP-HH0RPGN.3516.3 +3 -0
  8. runs/Jul02_02-32-29_DESKTOP-HH0RPGN/events.out.tfevents.1719862355.DESKTOP-HH0RPGN.3516.4 +3 -0
  9. runs/Jul02_02-32-29_DESKTOP-HH0RPGN/events.out.tfevents.1719862656.DESKTOP-HH0RPGN.3516.5 +3 -0
  10. runs/Jul02_02-37-36_DESKTOP-HH0RPGN/events.out.tfevents.1719862662.DESKTOP-HH0RPGN.3516.6 +3 -0
  11. runs/Jul02_02-47-10_DESKTOP-HH0RPGN/events.out.tfevents.1719863236.DESKTOP-HH0RPGN.16244.0 +3 -0
  12. runs/Jul02_02-47-10_DESKTOP-HH0RPGN/events.out.tfevents.1719865170.DESKTOP-HH0RPGN.16244.1 +3 -0
  13. runs/Jul02_03-19-30_DESKTOP-HH0RPGN/events.out.tfevents.1719865176.DESKTOP-HH0RPGN.16244.2 +3 -0
  14. runs/Jul02_03-30-03_DESKTOP-HH0RPGN/events.out.tfevents.1719865809.DESKTOP-HH0RPGN.25208.0 +3 -0
  15. runs/Jul02_03-34-25_DESKTOP-HH0RPGN/events.out.tfevents.1719866070.DESKTOP-HH0RPGN.20036.0 +3 -0
  16. runs/Jul02_03-36-41_DESKTOP-HH0RPGN/events.out.tfevents.1719866206.DESKTOP-HH0RPGN.10528.0 +3 -0
  17. runs/Jul02_03-38-00_DESKTOP-HH0RPGN/events.out.tfevents.1719866285.DESKTOP-HH0RPGN.23520.0 +3 -0
  18. special_tokens_map.json +49 -5
  19. tokenizer.json +0 -0
  20. tokenizer_config.json +22 -20
  21. training_args.bin +1 -1
README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [w11wo/indonesian-roberta-base-sentiment-classifier](https://huggingface.co/w11wo/indonesian-roberta-base-sentiment-classifier) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8793
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- - Accuracy: 0.6842
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  ## Model description
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@@ -37,26 +37,25 @@ 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
43
  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 10
 
47
 
48
  ### Training results
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50
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.5782 | 1.25 | 50 | 0.6230 | 0.7237 |
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- | 0.4206 | 2.5 | 100 | 0.5538 | 0.6842 |
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- | 0.1611 | 3.75 | 150 | 0.6425 | 0.6974 |
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- | 0.0803 | 5.0 | 200 | 0.7506 | 0.7105 |
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- | 0.0571 | 6.25 | 250 | 0.9081 | 0.6842 |
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- | 0.0222 | 7.5 | 300 | 1.0240 | 0.6842 |
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- | 0.0132 | 8.75 | 350 | 0.9939 | 0.6579 |
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- | 0.0275 | 10.0 | 400 | 0.8793 | 0.6842 |
60
 
61
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [w11wo/indonesian-roberta-base-sentiment-classifier](https://huggingface.co/w11wo/indonesian-roberta-base-sentiment-classifier) on the None dataset.
19
  It achieves the following results on the evaluation set:
20
+ - Loss: 0.3747
21
+ - Accuracy: 0.8065
22
 
23
  ## Model description
24
 
 
37
  ### Training hyperparameters
38
 
39
  The following hyperparameters were used during training:
40
+ - learning_rate: 1e-05
41
  - train_batch_size: 8
42
  - eval_batch_size: 8
43
  - seed: 42
44
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
45
  - lr_scheduler_type: linear
46
+ - num_epochs: 8
47
+ - mixed_precision_training: Native AMP
48
 
49
  ### Training results
50
 
51
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
53
+ | 0.7012 | 1.32 | 50 | 0.6762 | 0.7527 |
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+ | 0.6653 | 2.63 | 100 | 0.6082 | 0.7849 |
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+ | 0.5322 | 3.95 | 150 | 0.4744 | 0.7957 |
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+ | 0.3976 | 5.26 | 200 | 0.4062 | 0.8387 |
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+ | 0.2965 | 6.58 | 250 | 0.3775 | 0.8065 |
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+ | 0.2743 | 7.89 | 300 | 0.3747 | 0.8065 |
 
 
59
 
60
 
61
  ### Framework versions
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