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LogischeIP
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SentimentT2

Text Classification
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distilbert
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End of training

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  1. README.md +18 -17
  2. model.safetensors +1 -1
  3. runs/Jan10_17-30-46_032b48ce4f7d/events.out.tfevents.1704907847.032b48ce4f7d.692.42 +2 -2
  4. runs/Jan10_17-43-44_032b48ce4f7d/events.out.tfevents.1704908624.032b48ce4f7d.692.43 +3 -0
  5. runs/Jan10_17-57-04_032b48ce4f7d/events.out.tfevents.1704909425.032b48ce4f7d.692.44 +3 -0
  6. runs/Jan10_18-14-28_032b48ce4f7d/events.out.tfevents.1704910469.032b48ce4f7d.692.45 +3 -0
  7. runs/Jan10_18-19-16_032b48ce4f7d/events.out.tfevents.1704910757.032b48ce4f7d.692.46 +3 -0
  8. runs/Jan10_18-27-09_032b48ce4f7d/events.out.tfevents.1704911230.032b48ce4f7d.692.47 +3 -0
  9. training_args.bin +1 -1
README.md CHANGED
@@ -18,11 +18,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.8793
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- - Accuracy: 0.7143
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- - F1: 0.7099
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- - Auc Roc: 0.8948
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- - Log Loss: 1.8793
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  ## Model description
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@@ -42,27 +42,28 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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- - train_batch_size: 32
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- - eval_batch_size: 32
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  - 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
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Auc Roc | Log Loss |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:-------:|:--------:|
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- | No log | 1.0 | 8 | 1.7750 | 0.7429 | 0.7448 | 0.8959 | 1.7750 |
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- | No log | 2.0 | 16 | 1.9519 | 0.6857 | 0.6896 | 0.8992 | 1.9519 |
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- | No log | 3.0 | 24 | 1.8079 | 0.7286 | 0.7293 | 0.8990 | 1.8079 |
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- | No log | 4.0 | 32 | 1.8638 | 0.6714 | 0.6745 | 0.8975 | 1.8638 |
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- | No log | 5.0 | 40 | 1.9660 | 0.6714 | 0.6656 | 0.9049 | 1.9660 |
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- | No log | 6.0 | 48 | 1.9401 | 0.7143 | 0.7042 | 0.8977 | 1.9401 |
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- | No log | 7.0 | 56 | 1.9271 | 0.7 | 0.6934 | 0.8911 | 1.9271 |
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- | No log | 8.0 | 64 | 1.9025 | 0.7 | 0.6930 | 0.8896 | 1.9025 |
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- | No log | 9.0 | 72 | 1.8840 | 0.7143 | 0.7099 | 0.8942 | 1.8840 |
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- | No log | 10.0 | 80 | 1.8793 | 0.7143 | 0.7099 | 0.8948 | 1.8793 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 5.1316
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+ - Accuracy: 0.6143
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+ - F1: 0.6141
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+ - Auc Roc: 0.8480
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+ - Log Loss: 4.8354
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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+ - train_batch_size: 40
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+ - eval_batch_size: 10
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  - 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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+ - lr_scheduler_warmup_ratio: 0.1
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  - num_epochs: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Auc Roc | Log Loss |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:-------:|:--------:|
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+ | No log | 1.0 | 7 | 4.9260 | 0.5714 | 0.5720 | 0.8449 | 4.7441 |
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+ | No log | 2.0 | 14 | 5.0398 | 0.5857 | 0.5850 | 0.8463 | 4.8234 |
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+ | No log | 3.0 | 21 | 5.0899 | 0.6 | 0.5983 | 0.8457 | 4.8482 |
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+ | No log | 4.0 | 28 | 5.1227 | 0.6 | 0.5983 | 0.8471 | 4.8646 |
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+ | No log | 5.0 | 35 | 5.1350 | 0.6 | 0.5983 | 0.8473 | 4.8639 |
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+ | No log | 6.0 | 42 | 5.1155 | 0.6143 | 0.6141 | 0.8477 | 4.8342 |
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+ | No log | 7.0 | 49 | 5.1197 | 0.6143 | 0.6141 | 0.8475 | 4.8321 |
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+ | No log | 8.0 | 56 | 5.1254 | 0.6143 | 0.6141 | 0.8476 | 4.8331 |
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+ | No log | 9.0 | 63 | 5.1317 | 0.6143 | 0.6141 | 0.8480 | 4.8364 |
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+ | 0.0 | 10.0 | 70 | 5.1316 | 0.6143 | 0.6141 | 0.8480 | 4.8354 |
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  ### Framework versions
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