Uploading best model based on F1 score

README.md

@@ -0,0 +1,79 @@
+---
+library_name: transformers
+base_model: FacebookAI/xlm-roberta-large-finetuned-conll03-english
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: xlm-roberta-large-finetuned-conll03-english-finetuned-ner-biomedical-spanish
+  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. -->
+
+# xlm-roberta-large-finetuned-conll03-english-finetuned-ner-biomedical-spanish
+
+This model is a fine-tuned version of [FacebookAI/xlm-roberta-large-finetuned-conll03-english](https://huggingface.co/FacebookAI/xlm-roberta-large-finetuned-conll03-english) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1526
+- Precision: 0.8568
+- Recall: 0.8258
+- F1: 0.8410
+- Accuracy: 0.9542
+
+## 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
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 32
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 200
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 379  | 0.8877          | 0.5421    | 0.4232 | 0.4754 | 0.7697   |
+| 0.8712        | 2.0   | 758  | 0.7159          | 0.5625    | 0.4761 | 0.5157 | 0.8265   |
+| 0.1507        | 3.0   | 1137 | 0.4917          | 0.6528    | 0.5265 | 0.5829 | 0.8724   |
+| 0.0984        | 4.0   | 1516 | 0.3969          | 0.7123    | 0.6516 | 0.6806 | 0.9005   |
+| 0.0984        | 5.0   | 1895 | 0.3112          | 0.7463    | 0.6452 | 0.6920 | 0.9090   |
+| 0.0732        | 6.0   | 2274 | 0.2653          | 0.8166    | 0.7239 | 0.7674 | 0.9299   |
+| 0.0561        | 7.0   | 2653 | 0.2200          | 0.8006    | 0.7148 | 0.7553 | 0.9308   |
+| 0.0465        | 8.0   | 3032 | 0.1590          | 0.8451    | 0.7884 | 0.8158 | 0.9485   |
+| 0.0465        | 9.0   | 3411 | 0.1526          | 0.8568    | 0.8258 | 0.8410 | 0.9542   |
+| 0.0396        | 10.0  | 3790 | 0.1494          | 0.8493    | 0.8142 | 0.8314 | 0.9526   |
+
+
+### Framework versions
+
+- Transformers 4.46.3
+- Pytorch 2.5.1+cu121
+- Datasets 3.1.0
+- Tokenizers 0.20.3

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:89a99300380899739e45cc860d1055d13d3fefbfeb1fccc032b29d5ff83bf95c
+oid sha256:b2b5d01690011e76602054e05cb54b1ec245fa4a50cf82a23a09596a0965ff3b
 size 2235612764