End of training

README.md

@@ -0,0 +1,70 @@
+---
+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
+  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
+
+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: 0.0731
+- Micro Precision: 0.7189
+- Micro Recall: 0.5774
+- Micro F1: 0.6404
+- Macro Precision: 0.6049
+- Macro Recall: 0.4433
+- Macro F1: 0.4898
+- Weighted Precision: 0.7004
+- Weighted Recall: 0.5774
+- Weighted F1: 0.6243
+- Hamming Loss: 0.0276
+
+## 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   | 11118 | 0.0765          | 0.7647          | 0.5046       | 0.6080   | 0.6047          | 0.3580       | 0.4127   | 0.7321             | 0.5046          | 0.5764      | 0.0277       |
+| No log        | 2.0   | 22236 | 0.0733          | 0.7309          | 0.5344       | 0.6174   | 0.5791          | 0.4162       | 0.4611   | 0.7105             | 0.5344          | 0.5923      | 0.0282       |
+| No log        | 3.0   | 33354 | 0.0731          | 0.7189          | 0.5774       | 0.6404   | 0.6049          | 0.4433       | 0.4898   | 0.7004             | 0.5774          | 0.6243      | 0.0276       |
+
+
+### Framework versions
+
+- Transformers 4.47.0
+- Pytorch 2.3.1+cu121
+- Datasets 2.20.0
+- Tokenizers 0.21.0