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EMOTION-AI

Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
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  1. README.md +13 -11
  2. model.safetensors +1 -1
README.md CHANGED
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  ---
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  library_name: transformers
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  license: apache-2.0
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- base_model: google-bert/bert-base-uncased
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  tags:
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  - generated_from_trainer
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  metrics:
@@ -16,10 +16,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # EMOTION-AI
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- This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.4188
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- - Accuracy: 0.5669
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.0002
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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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  - gradient_accumulation_steps: 4
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  - total_train_batch_size: 128
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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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- - num_epochs: 2
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 272 | 1.4966 | 0.5462 |
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- | 6.0068 | 1.9945 | 542 | 1.4188 | 0.5669 |
 
 
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  ### Framework versions
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- - Transformers 4.48.0.dev0
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  - Pytorch 2.4.1+cu121
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  - Datasets 3.2.0
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- - Tokenizers 0.21.0
 
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  ---
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  library_name: transformers
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  license: apache-2.0
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+ base_model: distilbert/distilbert-base-uncased
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  tags:
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  - generated_from_trainer
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  metrics:
 
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  # EMOTION-AI
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+ This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/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: 1.4780
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+ - Accuracy: 0.5616
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  ## Model description
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  ### Training hyperparameters
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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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  - gradient_accumulation_steps: 4
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  - total_train_batch_size: 128
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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: 4
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|
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+ | No log | 0.9982 | 271 | 1.5711 | 0.5464 |
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+ | 1.5442 | 2.0 | 543 | 1.4952 | 0.5638 |
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+ | 1.5442 | 2.9982 | 814 | 1.4755 | 0.5657 |
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+ | 1.3192 | 3.9926 | 1084 | 1.4780 | 0.5616 |
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  ### Framework versions
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+ - Transformers 4.44.2
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  - Pytorch 2.4.1+cu121
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  - Datasets 3.2.0
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+ - Tokenizers 0.19.1
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