End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: distilbert/distilroberta-base
+tags:
+- generated_from_trainer
+model-index:
+- name: augmented-go-emotions-plus-other-datasets-fine-tuned-distilroberta-v2
+  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. -->
+
+# augmented-go-emotions-plus-other-datasets-fine-tuned-distilroberta-v2
+
+This model is a fine-tuned version of [distilbert/distilroberta-base](https://huggingface.co/distilbert/distilroberta-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0792
+- Micro Precision: 0.6922
+- Micro Recall: 0.5854
+- Micro F1: 0.6343
+- Macro Precision: 0.5809
+- Macro Recall: 0.4729
+- Macro F1: 0.5136
+- Weighted Precision: 0.6764
+- Weighted Recall: 0.5854
+- Weighted F1: 0.6238
+- Hamming Loss: 0.0287
+
+## 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: Use OptimizerNames.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: 3.0
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Micro Precision | Micro Recall | Micro F1 | Macro Precision | Macro Recall | Macro F1 | Weighted Precision | Weighted Recall | Weighted F1 | Hamming Loss |
+|:-------------:|:-----:|:-----:|:---------------:|:---------------:|:------------:|:--------:|:---------------:|:------------:|:--------:|:------------------:|:---------------:|:-----------:|:------------:|
+| No log        | 1.0   | 18858 | 0.0745          | 0.7528          | 0.5169       | 0.6129   | 0.6155          | 0.3805       | 0.4336   | 0.7386             | 0.5169          | 0.5827      | 0.0278       |
+| No log        | 2.0   | 37716 | 0.0757          | 0.7102          | 0.5616       | 0.6272   | 0.5937          | 0.4658       | 0.5049   | 0.6978             | 0.5616          | 0.6105      | 0.0284       |
+| No log        | 3.0   | 56574 | 0.0792          | 0.6922          | 0.5854       | 0.6343   | 0.5809          | 0.4729       | 0.5136   | 0.6764             | 0.5854          | 0.6238      | 0.0287       |
+
+
+### Framework versions
+
+- Transformers 4.47.0
+- Pytorch 2.3.1+cu121
+- Datasets 2.20.0
+- Tokenizers 0.21.0