End of training

README.md

@@ -1,75 +1,84 @@
----
-datasets:
-- yelp_review_full
-license: apache-2.0
-metrics:
-- accuracy
-tags:
-- generated_from_trainer
-model-index:
-- name: mi-super-modelo
-  results:
-  - task:
-      type: text-classification
-      name: Text Classification
-    dataset:
-      name: yelp_review_full
-      type: yelp_review_full
-      config: yelp_review_full
-      split: test
-      args: yelp_review_full
-    metrics:
-    - type: accuracy
-      value: 0.225
-      name: Accuracy
----
-
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
-
-# mi-super-modelo
-
-This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the yelp_review_full dataset.
-It achieves the following results on the evaluation set:
-- Loss: 1.6404
-- Accuracy: 0.225
-
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
-
-### Training hyperparameters
-
-The following hyperparameters were used during training:
-- learning_rate: 5e-05
-- train_batch_size: 8
-- eval_batch_size: 8
-- seed: 42
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- num_epochs: 1
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.7058        | 0.5   | 5    | 1.7046          | 0.225    |
-| 1.6208        | 1.0   | 10   | 1.6404          | 0.225    |
-
-
-### Framework versions
-
-- Transformers 4.30.2
-- Pytorch 2.0.1+cu118
-- Datasets 2.13.1
-- Tokenizers 0.13.3
+---
+library_name: transformers
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: mi-super-modelo
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# mi-super-modelo
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3218
+- Accuracy: 0.87
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.7166        | 0.04  | 5    | 0.6899          | 0.5      |
+| 0.6804        | 0.08  | 10   | 0.6806          | 0.505    |
+| 0.6756        | 0.12  | 15   | 0.6625          | 0.565    |
+| 0.6527        | 0.16  | 20   | 0.6229          | 0.67     |
+| 0.6245        | 0.2   | 25   | 0.6537          | 0.585    |
+| 0.6079        | 0.24  | 30   | 0.5368          | 0.76     |
+| 0.5977        | 0.28  | 35   | 0.4603          | 0.83     |
+| 0.3683        | 0.32  | 40   | 0.5971          | 0.71     |
+| 0.3948        | 0.36  | 45   | 0.4346          | 0.815    |
+| 0.4459        | 0.4   | 50   | 0.4177          | 0.81     |
+| 0.5583        | 0.44  | 55   | 0.3364          | 0.855    |
+| 0.5495        | 0.48  | 60   | 0.3367          | 0.865    |
+| 0.1608        | 0.52  | 65   | 0.3992          | 0.825    |
+| 0.4232        | 0.56  | 70   | 0.3484          | 0.835    |
+| 0.6385        | 0.6   | 75   | 0.3930          | 0.86     |
+| 0.2918        | 0.64  | 80   | 0.3389          | 0.86     |
+| 0.2137        | 0.68  | 85   | 0.3272          | 0.865    |
+| 0.419         | 0.72  | 90   | 0.3188          | 0.885    |
+| 0.2032        | 0.76  | 95   | 0.3158          | 0.87     |
+| 0.226         | 0.8   | 100  | 0.3204          | 0.87     |
+| 0.2525        | 0.84  | 105  | 0.3398          | 0.83     |
+| 0.2573        | 0.88  | 110  | 0.3494          | 0.85     |
+| 0.3895        | 0.92  | 115  | 0.3368          | 0.835    |
+| 0.2776        | 0.96  | 120  | 0.3241          | 0.87     |
+| 0.2487        | 1.0   | 125  | 0.3218          | 0.87     |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cpu
+- Datasets 2.21.0
+- Tokenizers 0.19.1