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agomberto
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my_fancy_model

Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
Inference Endpoints
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agomberto commited on
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  1. README.md +13 -9
  2. loss.json +9 -9
  3. model.safetensors +1 -1
  4. training_args.bin +1 -1
README.md CHANGED
@@ -5,6 +5,8 @@ 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: my_fancy_model
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  results: []
@@ -17,8 +19,10 @@ should probably proofread and complete it, then remove this comment. -->
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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: 0.2538
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- - Accuracy: 0.85
 
 
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  ## Model description
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@@ -47,13 +51,13 @@ The following hyperparameters were used during training:
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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 | 7 | 0.4392 | 0.85 |
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- | No log | 2.0 | 14 | 0.3709 | 0.85 |
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- | No log | 3.0 | 21 | 0.3180 | 0.85 |
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- | No log | 4.0 | 28 | 0.2727 | 0.85 |
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- | No log | 5.0 | 35 | 0.2538 | 0.85 |
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  ### Framework versions
 
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  - generated_from_trainer
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  metrics:
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  - accuracy
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+ - recall
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+ - precision
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  model-index:
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  - name: my_fancy_model
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  results: []
 
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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: 0.3296
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+ - Accuracy: 0.9
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+ - Recall: 0.5
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+ - Precision: 0.45
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | Precision |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|
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+ | No log | 1.0 | 7 | 0.3508 | 0.9 | 0.5 | 0.45 |
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+ | No log | 2.0 | 14 | 0.3491 | 0.9 | 0.5 | 0.45 |
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+ | No log | 3.0 | 21 | 0.3379 | 0.9 | 0.5 | 0.45 |
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+ | No log | 4.0 | 28 | 0.3296 | 0.9 | 0.5 | 0.45 |
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+ | No log | 5.0 | 35 | 0.3365 | 0.85 | 0.4722 | 0.4474 |
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  ### Framework versions
loss.json CHANGED
@@ -3,28 +3,28 @@
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  "eval": [
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  {
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  "epoch": 1.0,
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- "accuracy": 0.85,
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- "loss": 0.4392448365688324
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  },
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- "accuracy": 0.85,
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  {
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  "epoch": 3.0,
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- "accuracy": 0.85,
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- "loss": 0.3180195391178131
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  },
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  {
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  "epoch": 4.0,
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- "accuracy": 0.85,
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- "loss": 0.27274245023727417
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  },
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  {
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  "epoch": 5.0,
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  "accuracy": 0.85,
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- "loss": 0.2538265287876129
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  }
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  ]
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  }
 
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  "eval": [
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  {
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  "epoch": 1.0,
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+ "accuracy": 0.9,
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+ "loss": 0.35080939531326294
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  },
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  {
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  "epoch": 2.0,
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+ "accuracy": 0.9,
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+ "loss": 0.3490695059299469
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  {
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  "epoch": 3.0,
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+ "accuracy": 0.9,
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  {
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  "epoch": 4.0,
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+ "accuracy": 0.9,
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  {
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  "epoch": 5.0,
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  "accuracy": 0.85,
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+ "loss": 0.3364652991294861
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  }
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  ]
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  }
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