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distilbert-base-uncased-finetuned-emotion

Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
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update model card README.md

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@@ -23,10 +23,10 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.8885
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  - name: F1
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  type: f1
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- value: 0.8833012816215238
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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
@@ -36,9 +36,9 @@ 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 the emotion dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3817
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- - Accuracy: 0.8885
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- - F1: 0.8833
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  ## Model description
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@@ -63,14 +63,17 @@ The following hyperparameters were used during training:
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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: 2
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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- | No log | 1.0 | 125 | 0.6098 | 0.7935 | 0.7465 |
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- | 0.7784 | 2.0 | 250 | 0.3817 | 0.8885 | 0.8833 |
 
 
 
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9345
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  - name: F1
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  type: f1
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+ value: 0.9344638918723668
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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 [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: 0.1514
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+ - Accuracy: 0.9345
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+ - F1: 0.9345
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  ## Model description
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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: 5
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | No log | 1.0 | 125 | 0.4448 | 0.879 | 0.8713 |
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+ | 0.6963 | 2.0 | 250 | 0.2099 | 0.922 | 0.9225 |
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+ | 0.6963 | 3.0 | 375 | 0.1763 | 0.932 | 0.9324 |
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+ | 0.1548 | 4.0 | 500 | 0.1560 | 0.932 | 0.9318 |
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+ | 0.1548 | 5.0 | 625 | 0.1514 | 0.9345 | 0.9345 |
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  ### Framework versions