End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
+datasets:
+- hatexplain
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: distilbert-hatexplain
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: hatexplain
+      type: hatexplain
+      config: plain_text
+      split: validation
+      args: plain_text
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.6990644490644491
+    - name: Precision
+      type: precision
+      value: 0.6974890380019948
+    - name: Recall
+      type: recall
+      value: 0.6990644490644491
+    - name: F1
+      type: f1
+      value: 0.6978790945993021
+---
+
+<!-- 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. -->
+
+# distilbert-hatexplain
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the hatexplain dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8165
+- Accuracy: 0.6991
+- Precision: 0.6975
+- Recall: 0.6991
+- F1: 0.6979
+
+## 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: 2e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.6131        | 1.0   | 1923 | 0.7399          | 0.6925   | 0.6877    | 0.6925 | 0.6847 |
+| 0.7386        | 2.0   | 3846 | 0.7254          | 0.7040   | 0.7033    | 0.7040 | 0.7036 |
+| 0.6471        | 3.0   | 5769 | 0.8259          | 0.7019   | 0.6995    | 0.7019 | 0.7005 |
+
+
+### Framework versions
+
+- Transformers 4.47.0
+- Pytorch 2.5.1+cu118
+- Datasets 3.1.0
+- Tokenizers 0.21.0