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scenario-NON-KD-PR-COPY-CDF-ALL-D2_data-cardiffnlp_tweet_sentiment_multilingual_

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deberta-v2
Generated from Trainer
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  1. README.md +54 -54
  2. eval_results_cardiff.json +1 -1
  3. model.safetensors +1 -1
  4. training_args.bin +1 -1
README.md CHANGED
@@ -1,14 +1,14 @@
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  ---
 
 
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  base_model: microsoft/mdeberta-v3-base
 
 
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  datasets:
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  - tweet_sentiment_multilingual
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- library_name: transformers
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- license: mit
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  metrics:
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  - accuracy
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  - f1
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- tags:
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- - generated_from_trainer
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  model-index:
13
  - name: scenario-NON-KD-PR-COPY-CDF-ALL-D2_data-cardiffnlp_tweet_sentiment_multilingual_
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  results: []
@@ -21,9 +21,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on the tweet_sentiment_multilingual dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 5.1517
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- - Accuracy: 0.5571
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- - F1: 0.5567
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  ## Model description
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@@ -45,7 +45,7 @@ The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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  - train_batch_size: 32
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  - eval_batch_size: 32
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- - seed: 44
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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: 50
@@ -54,52 +54,52 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-------:|:-----:|:---------------:|:--------:|:------:|
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- | 1.0024 | 1.0870 | 500 | 0.9815 | 0.5556 | 0.5555 |
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- | 0.8411 | 2.1739 | 1000 | 0.9889 | 0.5772 | 0.5763 |
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- | 0.6502 | 3.2609 | 1500 | 1.1977 | 0.5633 | 0.5598 |
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- | 0.4723 | 4.3478 | 2000 | 1.6466 | 0.5617 | 0.5626 |
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- | 0.3276 | 5.4348 | 2500 | 1.7205 | 0.5498 | 0.5519 |
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- | 0.2221 | 6.5217 | 3000 | 2.0190 | 0.5590 | 0.5600 |
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- | 0.167 | 7.6087 | 3500 | 2.5446 | 0.5552 | 0.5562 |
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- | 0.1317 | 8.6957 | 4000 | 2.5112 | 0.5525 | 0.5539 |
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- | 0.1141 | 9.7826 | 4500 | 2.6152 | 0.5594 | 0.5545 |
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- | 0.1007 | 10.8696 | 5000 | 3.2079 | 0.5513 | 0.5416 |
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- | 0.0827 | 11.9565 | 5500 | 2.7099 | 0.5590 | 0.5590 |
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- | 0.0653 | 13.0435 | 6000 | 3.1595 | 0.5721 | 0.5678 |
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- | 0.0644 | 14.1304 | 6500 | 3.1304 | 0.5679 | 0.5667 |
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- | 0.054 | 15.2174 | 7000 | 3.0885 | 0.5590 | 0.5573 |
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- | 0.0504 | 16.3043 | 7500 | 3.5769 | 0.5583 | 0.5580 |
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- | 0.0394 | 17.3913 | 8000 | 3.5597 | 0.5606 | 0.5608 |
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- | 0.0419 | 18.4783 | 8500 | 3.8739 | 0.5525 | 0.5501 |
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- | 0.0406 | 19.5652 | 9000 | 3.5220 | 0.5667 | 0.5660 |
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- | 0.0355 | 20.6522 | 9500 | 4.0325 | 0.5691 | 0.5667 |
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- | 0.0281 | 21.7391 | 10000 | 3.7630 | 0.5602 | 0.5614 |
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- | 0.0266 | 22.8261 | 10500 | 4.0162 | 0.5617 | 0.5553 |
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- | 0.0283 | 23.9130 | 11000 | 3.9135 | 0.5525 | 0.5529 |
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- | 0.027 | 25.0 | 11500 | 4.0734 | 0.5563 | 0.5541 |
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- | 0.0205 | 26.0870 | 12000 | 4.2900 | 0.5583 | 0.5586 |
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- | 0.0198 | 27.1739 | 12500 | 4.2693 | 0.5579 | 0.5572 |
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- | 0.0155 | 28.2609 | 13000 | 4.7029 | 0.5563 | 0.5435 |
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- | 0.0187 | 29.3478 | 13500 | 4.4409 | 0.5640 | 0.5616 |
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- | 0.014 | 30.4348 | 14000 | 4.4588 | 0.5571 | 0.5568 |
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- | 0.0147 | 31.5217 | 14500 | 4.3420 | 0.5652 | 0.5640 |
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- | 0.0128 | 32.6087 | 15000 | 4.5721 | 0.5598 | 0.5575 |
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- | 0.0099 | 33.6957 | 15500 | 4.5574 | 0.5586 | 0.5599 |
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- | 0.0101 | 34.7826 | 16000 | 4.3777 | 0.5610 | 0.5613 |
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- | 0.0053 | 35.8696 | 16500 | 4.8103 | 0.5610 | 0.5617 |
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- | 0.0107 | 36.9565 | 17000 | 4.2925 | 0.5590 | 0.5589 |
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- | 0.0081 | 38.0435 | 17500 | 4.5884 | 0.5606 | 0.5591 |
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- | 0.0071 | 39.1304 | 18000 | 4.7187 | 0.5617 | 0.5621 |
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- | 0.0075 | 40.2174 | 18500 | 4.7305 | 0.5594 | 0.5591 |
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- | 0.0081 | 41.3043 | 19000 | 4.5589 | 0.5602 | 0.5607 |
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- | 0.0059 | 42.3913 | 19500 | 4.6516 | 0.5598 | 0.5589 |
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- | 0.0061 | 43.4783 | 20000 | 4.6553 | 0.5613 | 0.5605 |
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- | 0.0032 | 44.5652 | 20500 | 4.9672 | 0.5567 | 0.5569 |
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- | 0.0031 | 45.6522 | 21000 | 5.0283 | 0.5590 | 0.5595 |
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- | 0.0032 | 46.7391 | 21500 | 5.0801 | 0.5563 | 0.5552 |
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- | 0.0032 | 47.8261 | 22000 | 5.0934 | 0.5602 | 0.5604 |
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- | 0.0017 | 48.9130 | 22500 | 5.1305 | 0.5579 | 0.5581 |
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- | 0.0017 | 50.0 | 23000 | 5.1517 | 0.5571 | 0.5567 |
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  ### Framework versions
 
1
  ---
2
+ library_name: transformers
3
+ license: mit
4
  base_model: microsoft/mdeberta-v3-base
5
+ tags:
6
+ - generated_from_trainer
7
  datasets:
8
  - tweet_sentiment_multilingual
 
 
9
  metrics:
10
  - accuracy
11
  - f1
 
 
12
  model-index:
13
  - name: scenario-NON-KD-PR-COPY-CDF-ALL-D2_data-cardiffnlp_tweet_sentiment_multilingual_
14
  results: []
 
21
 
22
  This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on the tweet_sentiment_multilingual dataset.
23
  It achieves the following results on the evaluation set:
24
+ - Loss: 5.0035
25
+ - Accuracy: 0.5625
26
+ - F1: 0.5617
27
 
28
  ## Model description
29
 
 
45
  - learning_rate: 5e-05
46
  - train_batch_size: 32
47
  - eval_batch_size: 32
48
+ - seed: 55
49
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
50
  - lr_scheduler_type: linear
51
  - num_epochs: 50
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-------:|:-----:|:---------------:|:--------:|:------:|
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+ | 1.021 | 1.0870 | 500 | 1.0027 | 0.5409 | 0.5367 |
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+ | 0.8432 | 2.1739 | 1000 | 1.0327 | 0.5814 | 0.5820 |
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+ | 0.6715 | 3.2609 | 1500 | 1.1554 | 0.5822 | 0.5778 |
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+ | 0.48 | 4.3478 | 2000 | 1.4182 | 0.5613 | 0.5573 |
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+ | 0.3384 | 5.4348 | 2500 | 1.8214 | 0.5567 | 0.5573 |
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+ | 0.2309 | 6.5217 | 3000 | 1.8385 | 0.5502 | 0.5445 |
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+ | 0.1737 | 7.6087 | 3500 | 2.0368 | 0.5444 | 0.5440 |
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+ | 0.1324 | 8.6957 | 4000 | 2.3667 | 0.5424 | 0.5414 |
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+ | 0.1132 | 9.7826 | 4500 | 2.0414 | 0.5509 | 0.5486 |
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+ | 0.1058 | 10.8696 | 5000 | 2.5673 | 0.5509 | 0.5491 |
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+ | 0.0833 | 11.9565 | 5500 | 2.7424 | 0.5513 | 0.5509 |
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+ | 0.0662 | 13.0435 | 6000 | 3.2582 | 0.5544 | 0.5529 |
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+ | 0.0664 | 14.1304 | 6500 | 3.5005 | 0.5556 | 0.5521 |
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+ | 0.0532 | 15.2174 | 7000 | 3.0692 | 0.5502 | 0.5509 |
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+ | 0.0494 | 16.3043 | 7500 | 3.1700 | 0.5478 | 0.5487 |
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+ | 0.0485 | 17.3913 | 8000 | 3.8948 | 0.5382 | 0.5377 |
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+ | 0.0359 | 18.4783 | 8500 | 3.5655 | 0.5583 | 0.5570 |
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+ | 0.0322 | 19.5652 | 9000 | 4.0121 | 0.5583 | 0.5547 |
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+ | 0.0294 | 20.6522 | 9500 | 3.5540 | 0.5579 | 0.5582 |
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+ | 0.026 | 21.7391 | 10000 | 4.0054 | 0.5525 | 0.5535 |
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+ | 0.0305 | 22.8261 | 10500 | 3.8289 | 0.5498 | 0.5453 |
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+ | 0.0232 | 23.9130 | 11000 | 4.4012 | 0.5556 | 0.5558 |
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+ | 0.0209 | 25.0 | 11500 | 4.0916 | 0.5559 | 0.5504 |
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+ | 0.0224 | 26.0870 | 12000 | 4.3087 | 0.5586 | 0.5583 |
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+ | 0.0192 | 27.1739 | 12500 | 4.0617 | 0.5467 | 0.5474 |
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+ | 0.0198 | 28.2609 | 13000 | 4.1456 | 0.5567 | 0.5555 |
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+ | 0.0148 | 29.3478 | 13500 | 4.5847 | 0.5505 | 0.5519 |
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+ | 0.016 | 30.4348 | 14000 | 4.3128 | 0.5494 | 0.5501 |
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+ | 0.0145 | 31.5217 | 14500 | 4.4021 | 0.5505 | 0.5500 |
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+ | 0.0146 | 32.6087 | 15000 | 4.3393 | 0.5509 | 0.5506 |
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+ | 0.0089 | 33.6957 | 15500 | 4.4852 | 0.5486 | 0.5499 |
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+ | 0.0089 | 34.7826 | 16000 | 4.8487 | 0.5475 | 0.5487 |
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+ | 0.0085 | 35.8696 | 16500 | 4.8052 | 0.5567 | 0.5573 |
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+ | 0.0077 | 36.9565 | 17000 | 4.6518 | 0.5502 | 0.5484 |
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+ | 0.0095 | 38.0435 | 17500 | 4.2742 | 0.5567 | 0.5554 |
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+ | 0.0054 | 39.1304 | 18000 | 4.7804 | 0.5548 | 0.5520 |
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+ | 0.0074 | 40.2174 | 18500 | 4.6940 | 0.5540 | 0.5516 |
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+ | 0.0053 | 41.3043 | 19000 | 4.6543 | 0.5590 | 0.5581 |
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+ | 0.003 | 42.3913 | 19500 | 5.0637 | 0.5563 | 0.5572 |
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+ | 0.0044 | 43.4783 | 20000 | 4.7918 | 0.5652 | 0.5657 |
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+ | 0.0053 | 44.5652 | 20500 | 4.7492 | 0.5625 | 0.5604 |
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+ | 0.0031 | 45.6522 | 21000 | 4.8642 | 0.5571 | 0.5567 |
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+ | 0.0026 | 46.7391 | 21500 | 4.9137 | 0.5617 | 0.5614 |
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+ | 0.0025 | 47.8261 | 22000 | 4.8985 | 0.5629 | 0.5626 |
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+ | 0.0007 | 48.9130 | 22500 | 4.9890 | 0.5633 | 0.5621 |
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+ | 0.0027 | 50.0 | 23000 | 5.0035 | 0.5625 | 0.5617 |
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  ### Framework versions
eval_results_cardiff.json CHANGED
@@ -1 +1 @@
1
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+ {"arabic": {"f1": 0.5505121631124021, "accuracy": 0.5482758620689655, "confusion_matrix": [[153, 106, 31], [74, 164, 52], [58, 72, 160]]}, "english": {"f1": 0.6252888515559376, "accuracy": 0.6229885057471264, "confusion_matrix": [[204, 75, 11], [84, 174, 32], [47, 79, 164]]}, "french": {"f1": 0.5844273689986265, "accuracy": 0.5850574712643678, "confusion_matrix": [[192, 50, 48], [46, 159, 85], [65, 67, 158]]}, "german": {"f1": 0.6770577974077062, "accuracy": 0.6770114942528735, "confusion_matrix": [[198, 62, 30], [55, 216, 19], [63, 52, 175]]}, "hindi": {"f1": 0.4860992225426562, "accuracy": 0.4885057471264368, "confusion_matrix": [[164, 56, 70], [100, 115, 75], [87, 57, 146]]}, "italian": {"f1": 0.5664004433041901, "accuracy": 0.5747126436781609, "confusion_matrix": [[110, 88, 92], [20, 200, 70], [23, 77, 190]]}, "portuguese": {"f1": 0.6162615581379695, "accuracy": 0.6137931034482759, "confusion_matrix": [[154, 110, 26], [56, 194, 40], [28, 76, 186]]}, "spanish": {"f1": 0.5890270816894922, "accuracy": 0.5896551724137931, "confusion_matrix": [[181, 77, 32], [80, 145, 65], [51, 52, 187]]}, "all": {"f1": 0.5881456796344003, "accuracy": 0.5875, "confusion_matrix": [[1356, 624, 340], [515, 1367, 438], [422, 532, 1366]]}}
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