End of training

README.md

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+---
+license: apache-2.0
+base_model: google/electra-base-discriminator
+tags:
+- generated_from_trainer
+metrics:
+- f1
+- accuracy
+- precision
+- recall
+model-index:
+- name: Electra_Hatespeech_Classifier5
+  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. -->
+
+# Electra_Hatespeech_Classifier5
+
+This model is a fine-tuned version of [google/electra-base-discriminator](https://huggingface.co/google/electra-base-discriminator) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2370
+- F1: 0.9484
+- Accuracy: 0.9629
+- Precision: 0.9540
+- Recall: 0.9428
+
+## 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: 16
+- eval_batch_size: 8
+- seed: 100
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 4
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | F1     | Accuracy | Precision | Recall |
+|:-------------:|:-----:|:-----:|:---------------:|:------:|:--------:|:---------:|:------:|
+| 0.2066        | 1.0   | 5084  | 0.2209          | 0.8904 | 0.9180   | 0.8624    | 0.9204 |
+| 0.1319        | 2.0   | 10168 | 0.1719          | 0.9290 | 0.9490   | 0.9363    | 0.9218 |
+| 0.0785        | 3.0   | 15252 | 0.2224          | 0.9409 | 0.9582   | 0.9617    | 0.9211 |
+| 0.0365        | 4.0   | 20336 | 0.2370          | 0.9484 | 0.9629   | 0.9540    | 0.9428 |
+
+
+### Framework versions
+
+- Transformers 4.39.3
+- Pytorch 2.1.2
+- Datasets 2.18.0
+- Tokenizers 0.15.2