End of training

README.md

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+---
+license: mit
+base_model: FacebookAI/roberta-base
+tags:
+- generated_from_trainer
+metrics:
+- f1
+- accuracy
+- precision
+- recall
+model-index:
+- name: RoBERTa_Hatespeech_Classifier
+  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. -->
+
+# RoBERTa_Hatespeech_Classifier
+
+This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2133
+- F1: 0.9156
+- Accuracy: 0.9388
+- Precision: 0.9144
+- Recall: 0.9168
+
+## 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: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 2
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | F1     | Accuracy | Precision | Recall |
+|:-------------:|:-----:|:-----:|:---------------:|:------:|:--------:|:---------:|:------:|
+| 0.2257        | 1.0   | 5084  | 0.2537          | 0.8900 | 0.9197   | 0.8820    | 0.8983 |
+| 0.1721        | 2.0   | 10168 | 0.2259          | 0.9123 | 0.9366   | 0.9123    | 0.9123 |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.0
+- Tokenizers 0.15.2

runs/Apr21_23-00-21_031ae2944efa/events.out.tfevents.1713744255.031ae2944efa.1300.3

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