End of training

README.md

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+---
+license: other
+library_name: peft
+tags:
+- generated_from_trainer
+base_model: meta-llama/Meta-Llama-3-8B
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: hubbub-sentiment_llama3
+  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. -->
+
+# hubbub-sentiment_llama3
+
+This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4586
+- Accuracy: 0.8269
+- Precision: 0.8234
+- Recall: 0.8269
+- F1: 0.8235
+
+## 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: 0.0002
+- train_batch_size: 4
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.821         | 0.9998 | 1406 | 0.8073          | 0.6595   | 0.7055    | 0.6595 | 0.5621 |
+| 0.7134        | 1.9996 | 2812 | 0.6063          | 0.7508   | 0.7422    | 0.7508 | 0.7427 |
+| 0.5814        | 2.9995 | 4218 | 0.4586          | 0.8269   | 0.8234    | 0.8269 | 0.8235 |
+
+
+### Framework versions
+
+- PEFT 0.10.0
+- Transformers 4.40.1
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.0
+- Tokenizers 0.19.1