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ramirces
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clasificador-dair-ai-emotion

Text Classification
Transformers
Safetensors
bert
classification
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
ramirces commited on
Commit
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1 Parent(s): 7c09a42

Training complete

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Files changed (4) hide show
  1. README.md +8 -8
  2. config.json +1 -1
  3. model.safetensors +1 -1
  4. training_args.bin +1 -1
README.md CHANGED
@@ -23,7 +23,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.9365
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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
@@ -33,8 +33,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the emotion dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2211
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- - Accuracy: 0.9365
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  ## Model description
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@@ -65,14 +65,14 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.2267 | 1.0 | 2000 | 0.1906 | 0.931 |
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- | 0.1558 | 2.0 | 4000 | 0.1894 | 0.9315 |
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- | 0.1032 | 3.0 | 6000 | 0.2211 | 0.9365 |
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  ### Framework versions
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- - Transformers 4.40.1
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  - Pytorch 2.2.1+cu121
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- - Datasets 2.19.0
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  - Tokenizers 0.19.1
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.931
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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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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the emotion dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2163
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+ - Accuracy: 0.931
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.2545 | 1.0 | 2000 | 0.2308 | 0.927 |
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+ | 0.1436 | 2.0 | 4000 | 0.1631 | 0.9335 |
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+ | 0.0972 | 3.0 | 6000 | 0.2163 | 0.931 |
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  ### Framework versions
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+ - Transformers 4.40.2
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  - Pytorch 2.2.1+cu121
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+ - Datasets 2.19.1
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  - Tokenizers 0.19.1
config.json CHANGED
@@ -36,7 +36,7 @@
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  "position_embedding_type": "absolute",
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  "problem_type": "single_label_classification",
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  "torch_dtype": "float32",
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- "transformers_version": "4.40.1",
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  "type_vocab_size": 2,
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  "use_cache": true,
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  "vocab_size": 30522
 
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  "position_embedding_type": "absolute",
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  "problem_type": "single_label_classification",
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  "torch_dtype": "float32",
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+ "transformers_version": "4.40.2",
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  "type_vocab_size": 2,
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  "use_cache": true,
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  "vocab_size": 30522
model.safetensors CHANGED
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