End of training

README.md

@@ -0,0 +1,63 @@
+---
+base_model: klue/roberta-large
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: mango-32-0.00002-fin
+  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. -->
+
+# mango-32-0.00002-fin
+
+This model is a fine-tuned version of [klue/roberta-large](https://huggingface.co/klue/roberta-large) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9681
+- Accuracy: 0.6635
+- F1: 0.6551
+
+## 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: 64
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| No log        | 1.0   | 233  | 0.9796          | 0.6529   | 0.6356 |
+| No log        | 2.0   | 466  | 0.9687          | 0.6541   | 0.6359 |
+| 1.0158        | 3.0   | 699  | 0.9681          | 0.6635   | 0.6551 |
+
+
+### Framework versions
+
+- Transformers 4.34.1
+- Pytorch 2.1.0a0+b5021ba
+- Datasets 2.6.2
+- Tokenizers 0.14.1