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End of training

Browse files
README.md CHANGED
@@ -3,26 +3,11 @@ license: apache-2.0
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  base_model: distilbert-base-uncased
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  tags:
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  - generated_from_trainer
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- datasets:
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- - emotion
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  metrics:
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  - accuracy
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  model-index:
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  - name: results
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- results:
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- - task:
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- name: Text Classification
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- type: text-classification
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- dataset:
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- name: emotion
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- type: emotion
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- config: split
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- split: validation
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- args: split
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- metrics:
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- - name: Accuracy
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- type: accuracy
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- value: 0.919
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -30,10 +15,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # results
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- This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotion dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4055
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- - Accuracy: 0.919
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  ## Model description
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@@ -52,22 +37,21 @@ 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: 8.42e-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: 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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- | 0.1735 | 1.0 | 1000 | 0.2957 | 0.919 |
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- | 0.1154 | 2.0 | 2000 | 0.2450 | 0.9305 |
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- | 0.072 | 3.0 | 3000 | 0.2936 | 0.935 |
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- | 0.032 | 4.0 | 4000 | 0.3145 | 0.938 |
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  ### Framework versions
 
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  base_model: distilbert-base-uncased
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  tags:
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  - generated_from_trainer
 
 
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  metrics:
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  - accuracy
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  model-index:
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  - name: results
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+ results: []
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  # results
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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: 0.8835
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+ - Accuracy: 0.6862
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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: 5e-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: 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: 3
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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 | 179 | 0.6302 | 0.6440 |
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+ | No log | 2.0 | 358 | 0.6395 | 0.6712 |
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+ | 0.4692 | 3.0 | 537 | 0.8529 | 0.6764 |
 
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  ### Framework versions
config.json CHANGED
@@ -8,23 +8,7 @@
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  "dim": 768,
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  "dropout": 0.1,
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  "hidden_dim": 3072,
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  "max_position_embeddings": 512,
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  "model_type": "distilbert",
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  "dim": 768,
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  "dropout": 0.1,
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  "max_position_embeddings": 512,
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