End of training

README.md

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+---
+license: mit
+base_model: xlm-roberta-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: 16class_all9k_promptcor_23nov23_xlm_robt_case
+  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. -->
+
+# 16class_all9k_promptcor_23nov23_xlm_robt_case
+
+This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1020
+- Accuracy: 0.9787
+
+## 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: 1e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 8
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 1.0707        | 1.0   | 1442  | 0.5981          | 0.8113   |
+| 0.5897        | 2.0   | 2884  | 0.3605          | 0.8954   |
+| 0.4212        | 3.0   | 4326  | 0.2835          | 0.9249   |
+| 0.3463        | 4.0   | 5768  | 0.2020          | 0.9498   |
+| 0.2749        | 5.0   | 7210  | 0.1751          | 0.9594   |
+| 0.2336        | 6.0   | 8652  | 0.1298          | 0.9716   |
+| 0.1906        | 7.0   | 10094 | 0.1186          | 0.9759   |
+| 0.1458        | 8.0   | 11536 | 0.1020          | 0.9787   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.1+cu121
+- Datasets 2.15.0
+- Tokenizers 0.15.0