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End of training

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  1. README.md +12 -8
  2. config.json +3 -3
  3. model.safetensors +1 -1
  4. training_args.bin +1 -1
README.md CHANGED
@@ -18,7 +18,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [AnonymousCS/populism_xlmr_large](https://huggingface.co/AnonymousCS/populism_xlmr_large) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5351
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  - Accuracy: 0.9647
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  - 1-f1: 0.0
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  - 1-recall: 0.0
@@ -42,9 +42,9 @@ 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: 1e-05
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- - train_batch_size: 64
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- - eval_batch_size: 64
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  - seed: 42
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  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
@@ -55,10 +55,14 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:----:|:--------:|:-----------:|:------------:|
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- | 0.5318 | 1.0 | 34 | 0.5346 | 0.9647 | 0.0 | 0.0 | 0.0 | 0.5 |
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- | 0.4905 | 2.0 | 68 | 0.5345 | 0.9647 | 0.0 | 0.0 | 0.0 | 0.5 |
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- | 0.6185 | 3.0 | 102 | 0.5352 | 0.9647 | 0.0 | 0.0 | 0.0 | 0.5 |
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- | 0.5179 | 4.0 | 136 | 0.5351 | 0.9647 | 0.0 | 0.0 | 0.0 | 0.5 |
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [AnonymousCS/populism_xlmr_large](https://huggingface.co/AnonymousCS/populism_xlmr_large) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1902
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  - Accuracy: 0.9647
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  - 1-f1: 0.0
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  - 1-recall: 0.0
 
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 3e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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  - seed: 42
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  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:----:|:--------:|:-----------:|:------------:|
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+ | 0.3248 | 1.0 | 135 | 0.2069 | 0.9647 | 0.0 | 0.0 | 0.0 | 0.5 |
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+ | 0.0192 | 2.0 | 270 | 0.1696 | 0.9647 | 0.0 | 0.0 | 0.0 | 0.5 |
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+ | 0.2926 | 3.0 | 405 | 0.1731 | 0.9647 | 0.0 | 0.0 | 0.0 | 0.5 |
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+ | 0.0098 | 4.0 | 540 | 0.1854 | 0.9647 | 0.0 | 0.0 | 0.0 | 0.5 |
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+ | 0.1438 | 5.0 | 675 | 0.1670 | 0.9647 | 0.0 | 0.0 | 0.0 | 0.5 |
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+ | 0.0188 | 6.0 | 810 | 0.1680 | 0.9647 | 0.0 | 0.0 | 0.0 | 0.5 |
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+ | 0.1571 | 7.0 | 945 | 0.1832 | 0.9647 | 0.0 | 0.0 | 0.0 | 0.5 |
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+ | 0.8236 | 8.0 | 1080 | 0.1902 | 0.9647 | 0.0 | 0.0 | 0.0 | 0.5 |
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  ### Framework versions
config.json CHANGED
@@ -3,12 +3,12 @@
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  "architectures": [
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  "XLMRobertaForSequenceClassification"
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  ],
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- "attention_probs_dropout_prob": 0.1,
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  "bos_token_id": 0,
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- "classifier_dropout": null,
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  "eos_token_id": 2,
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  "hidden_act": "gelu",
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- "hidden_dropout_prob": 0.1,
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  "hidden_size": 1024,
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  "initializer_range": 0.02,
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  "intermediate_size": 4096,
 
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  "architectures": [
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  "XLMRobertaForSequenceClassification"
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  ],
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+ "attention_probs_dropout_prob": 0.2,
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  "bos_token_id": 0,
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+ "classifier_dropout": 0.2,
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  "eos_token_id": 2,
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  "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.2,
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  "hidden_size": 1024,
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  "initializer_range": 0.02,
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  "intermediate_size": 4096,
model.safetensors CHANGED
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