End of training

README.md

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+---
+license: mit
+base_model: xlm-roberta-large
+tags:
+- generated_from_trainer
+datasets:
+- conll2003job
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: my_xlm-roberta-large-finetuned-conlljob04
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: conll2003job
+      type: conll2003job
+      config: conll2003job
+      split: validation
+      args: conll2003job
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.961673640167364
+    - name: Recall
+      type: recall
+      value: 0.9670144732413329
+    - name: F1
+      type: f1
+      value: 0.964336661911555
+    - name: Accuracy
+      type: accuracy
+      value: 0.9935750165491998
+---
+
+<!-- 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. -->
+
+# my_xlm-roberta-large-finetuned-conlljob04
+
+This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the conll2003job dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0420
+- Precision: 0.9617
+- Recall: 0.9670
+- F1: 0.9643
+- Accuracy: 0.9936
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 6
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.1566        | 1.0   | 896  | 0.0403          | 0.9425    | 0.9542 | 0.9483 | 0.9911   |
+| 0.0319        | 2.0   | 1792 | 0.0359          | 0.9523    | 0.9571 | 0.9547 | 0.9922   |
+| 0.0156        | 3.0   | 2688 | 0.0356          | 0.9594    | 0.9625 | 0.9609 | 0.9929   |
+| 0.01          | 4.0   | 3584 | 0.0377          | 0.9604    | 0.9672 | 0.9638 | 0.9934   |
+| 0.0058        | 5.0   | 4480 | 0.0398          | 0.9618    | 0.9662 | 0.9640 | 0.9934   |
+| 0.0034        | 6.0   | 5376 | 0.0420          | 0.9617    | 0.9670 | 0.9643 | 0.9936   |
+
+
+### Framework versions
+
+- Transformers 4.34.1
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.5
+- Tokenizers 0.14.1

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