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Icculus
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distilbert-base-uncased-finetuned-emotion-OXO

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Files changed (3) hide show
  1. README.md +10 -8
  2. model.safetensors +1 -1
  3. runs/Mar18_20-05-10_a32996070df1/events.out.tfevents.1710792314.a32996070df1.689.1 +2 -2
README.md CHANGED
@@ -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: 0.9215
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  - name: F1
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  type: f1
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- value: 0.9214443382181596
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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: 0.2232
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- - Accuracy: 0.9215
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- - F1: 0.9214
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  ## Model description
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@@ -63,14 +63,16 @@ 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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- | 0.8343 | 1.0 | 250 | 0.3262 | 0.9035 | 0.9024 |
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- | 0.2526 | 2.0 | 500 | 0.2232 | 0.9215 | 0.9214 |
 
 
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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: 0.9385
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  - name: F1
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  type: f1
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+ value: 0.9385929840555288
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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: 0.1494
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+ - Accuracy: 0.9385
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+ - F1: 0.9386
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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: 4
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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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+ | 0.8135 | 1.0 | 250 | 0.2793 | 0.9125 | 0.9124 |
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+ | 0.2141 | 2.0 | 500 | 0.1757 | 0.9305 | 0.9310 |
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+ | 0.1428 | 3.0 | 750 | 0.1578 | 0.936 | 0.9366 |
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+ | 0.1113 | 4.0 | 1000 | 0.1494 | 0.9385 | 0.9386 |
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  ### Framework versions
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