End of training

README.md

@@ -0,0 +1,73 @@
+---
+library_name: transformers
+base_model: raulgdp/xml-roberta-large-finetuned-ner
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: la-xml-roberta-large-ner-finetuned-biomedical-conT4-16
+  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. -->
+
+# la-xml-roberta-large-ner-finetuned-biomedical-conT4-16
+
+This model is a fine-tuned version of [raulgdp/xml-roberta-large-finetuned-ner](https://huggingface.co/raulgdp/xml-roberta-large-finetuned-ner) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0755
+- Precision: 0.9291
+- Recall: 0.9569
+- F1: 0.9428
+- Accuracy: 0.9798
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 2
+- 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: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 306  | 0.1016          | 0.9102    | 0.9308 | 0.9204 | 0.9711   |
+| 0.6706        | 2.0   | 612  | 0.0809          | 0.9237    | 0.9598 | 0.9414 | 0.9784   |
+| 0.6706        | 3.0   | 918  | 0.0696          | 0.9371    | 0.9612 | 0.9490 | 0.9817   |
+| 0.079         | 4.0   | 1224 | 0.0738          | 0.9318    | 0.9582 | 0.9448 | 0.9803   |
+| 0.0564        | 5.0   | 1530 | 0.0755          | 0.9291    | 0.9569 | 0.9428 | 0.9798   |
+
+
+### Framework versions
+
+- Transformers 4.46.2
+- 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:ff0a99f7845da9b9c3818dc4590302b5380152babd15283e88c0432fff1292d7
+oid sha256:373f2fa729bd55a3e4e71bfcdfd569f03cba80002913fbb1292c06cd3bde18b6
 size 2235534864