End of training

README.md

@@ -1,68 +1,74 @@
----
-library_name: transformers
-license: mit
-base_model: FacebookAI/xlm-roberta-large
-tags:
-- generated_from_trainer
-metrics:
-- precision
-- recall
-- f1
-- accuracy
-model-index:
-- name: NER-finetuning-xml-roberta-prostata
-  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. -->
-
-# NER-finetuning-xml-roberta-prostata
-
-This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the None dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.0423
-- Precision: 0.9600
-- Recall: 0.9595
-- F1: 0.9597
-- Accuracy: 0.9920
-
-## 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: 4
-- eval_batch_size: 4
-- seed: 42
-- 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
-- num_epochs: 2
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.3415        | 1.0   | 777  | 0.0487          | 0.9311    | 0.9353 | 0.9332 | 0.9890   |
-| 0.0486        | 2.0   | 1554 | 0.0295          | 0.9740    | 0.9683 | 0.9711 | 0.9945   |
-
-
-### Framework versions
-
-- Transformers 4.52.4
-- Pytorch 2.7.1+cu118
-- Datasets 3.6.0
-- Tokenizers 0.21.1
+---
+library_name: transformers
+license: mit
+base_model: FacebookAI/xlm-roberta-large
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: NER-finetuning-xml-roberta-prostata
+  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. -->
+
+# NER-finetuning-xml-roberta-prostata
+
+This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0304
+- Precision: 0.9616
+- Recall: 0.9635
+- F1: 0.9626
+- 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: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 8
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 98   | 0.0950          | 0.8240    | 0.9120 | 0.8657 | 0.9754   |
+| No log        | 2.0   | 196  | 0.0402          | 0.9401    | 0.9540 | 0.9470 | 0.9919   |
+| No log        | 3.0   | 294  | 0.0275          | 0.9587    | 0.9625 | 0.9606 | 0.9938   |
+| No log        | 4.0   | 392  | 0.0273          | 0.9629    | 0.9754 | 0.9691 | 0.9942   |
+| No log        | 5.0   | 490  | 0.0242          | 0.9716    | 0.9761 | 0.9738 | 0.9960   |
+| 0.1436        | 6.0   | 588  | 0.0255          | 0.9728    | 0.9735 | 0.9731 | 0.9959   |
+| 0.1436        | 7.0   | 686  | 0.0235          | 0.9773    | 0.9761 | 0.9767 | 0.9960   |
+| 0.1436        | 8.0   | 784  | 0.0223          | 0.9761    | 0.9767 | 0.9764 | 0.9961   |
+
+
+### Framework versions
+
+- Transformers 4.52.4
+- Pytorch 2.6.0+cu124
+- Datasets 3.6.0
+- Tokenizers 0.21.1

runs/Jun12_21-23-05_db55f322a086/events.out.tfevents.1749763978.db55f322a086.4136.1

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