End of training

README.md

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+---
+license: mit
+base_model: xlm-roberta-base
+tags:
+- generated_from_trainer
+datasets:
+- xtreme
+metrics:
+- f1
+model-index:
+- name: roberta-base-NER
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: xtreme
+      type: xtreme
+      config: PAN-X.en
+      split: validation
+      args: PAN-X.en
+    metrics:
+    - name: F1
+      type: f1
+      value: 0.7749031543995573
+---
+
+<!-- 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. -->
+
+# roberta-base-NER
+
+This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xtreme dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3068
+- F1: 0.7749
+
+## 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: 24
+- eval_batch_size: 24
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 2
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| No log        | 1.0   | 417  | 0.3361          | 0.7477 |
+| 0.5196        | 2.0   | 834  | 0.3068          | 0.7749 |
+
+
+### Framework versions
+
+- Transformers 4.33.0
+- Pytorch 2.0.0
+- Datasets 2.1.0
+- Tokenizers 0.13.3