Model save

README.md

@@ -0,0 +1,102 @@
+---
+library_name: transformers
+license: apache-2.0
+base_model: PlanTL-GOB-ES/bsc-bio-ehr-es
+tags:
+- generated_from_trainer
+datasets:
+- cantemist-85-ner
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: output
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: cantemist-85-ner
+      type: cantemist-85-ner
+      config: CantemistNer
+      split: validation
+      args: CantemistNer
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.8399232245681382
+    - name: Recall
+      type: recall
+      value: 0.8617565970854667
+    - name: F1
+      type: f1
+      value: 0.8506998444790046
+    - name: Accuracy
+      type: accuracy
+      value: 0.9916486929514279
+---
+
+<!-- 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. -->
+
+# output
+
+This model is a fine-tuned version of [PlanTL-GOB-ES/bsc-bio-ehr-es](https://huggingface.co/PlanTL-GOB-ES/bsc-bio-ehr-es) on the cantemist-85-ner dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0503
+- Precision: 0.8399
+- Recall: 0.8618
+- F1: 0.8507
+- Accuracy: 0.9916
+
+## 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: 5e-05
+- train_batch_size: 32
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10.0
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0542        | 1.0   | 511  | 0.0271          | 0.7485    | 0.7972 | 0.7721 | 0.9895   |
+| 0.0184        | 2.0   | 1022 | 0.0277          | 0.7897    | 0.8519 | 0.8196 | 0.9906   |
+| 0.0103        | 3.0   | 1533 | 0.0305          | 0.8238    | 0.8488 | 0.8361 | 0.9914   |
+| 0.0058        | 4.0   | 2044 | 0.0320          | 0.8197    | 0.8539 | 0.8364 | 0.9913   |
+| 0.0041        | 5.0   | 2555 | 0.0374          | 0.8397    | 0.8417 | 0.8407 | 0.9917   |
+| 0.0026        | 6.0   | 3066 | 0.0427          | 0.8368    | 0.8503 | 0.8435 | 0.9917   |
+| 0.0015        | 7.0   | 3577 | 0.0451          | 0.8207    | 0.8598 | 0.8398 | 0.9912   |
+| 0.0013        | 8.0   | 4088 | 0.0448          | 0.8318    | 0.8629 | 0.8471 | 0.9916   |
+| 0.0007        | 9.0   | 4599 | 0.0496          | 0.8399    | 0.8618 | 0.8507 | 0.9917   |
+| 0.0006        | 10.0  | 5110 | 0.0503          | 0.8399    | 0.8618 | 0.8507 | 0.9916   |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.0+cu121
+- Datasets 2.21.0
+- Tokenizers 0.19.1

model.safetensors

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tb/events.out.tfevents.1725572459.df0b2d2cc7fe.2457.0

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train.log

@@ -1549,3 +1549,16 @@ Training completed. Do not forget to share your model on huggingface.co/models =
 [INFO|trainer.py:2632] 2024-09-05 22:04:32,625 >> Loading best model from /content/dissertation/scripts/ner/output/checkpoint-4599 (score: 0.8506998444790046).
 
                                                   
 [INFO|trainer.py:4283] 2024-09-05 22:04:32,815 >> Waiting for the current checkpoint push to be finished, this might take a couple of minutes.
+[INFO|trainer.py:3503] 2024-09-05 22:04:37,739 >> Saving model checkpoint to /content/dissertation/scripts/ner/output
+[INFO|configuration_utils.py:472] 2024-09-05 22:04:37,741 >> Configuration saved in /content/dissertation/scripts/ner/output/config.json
+[INFO|modeling_utils.py:2799] 2024-09-05 22:04:39,388 >> Model weights saved in /content/dissertation/scripts/ner/output/model.safetensors
+[INFO|tokenization_utils_base.py:2684] 2024-09-05 22:04:39,389 >> tokenizer config file saved in /content/dissertation/scripts/ner/output/tokenizer_config.json
+[INFO|tokenization_utils_base.py:2693] 2024-09-05 22:04:39,390 >> Special tokens file saved in /content/dissertation/scripts/ner/output/special_tokens_map.json
+[INFO|trainer.py:3503] 2024-09-05 22:04:39,437 >> Saving model checkpoint to /content/dissertation/scripts/ner/output
+[INFO|configuration_utils.py:472] 2024-09-05 22:04:39,438 >> Configuration saved in /content/dissertation/scripts/ner/output/config.json
+[INFO|modeling_utils.py:2799] 2024-09-05 22:04:40,705 >> Model weights saved in /content/dissertation/scripts/ner/output/model.safetensors
+[INFO|tokenization_utils_base.py:2684] 2024-09-05 22:04:40,706 >> tokenizer config file saved in /content/dissertation/scripts/ner/output/tokenizer_config.json
+[INFO|tokenization_utils_base.py:2693] 2024-09-05 22:04:40,706 >> Special tokens file saved in /content/dissertation/scripts/ner/output/special_tokens_map.json
+{'eval_loss': 0.05025585740804672, 'eval_precision': 0.8399232245681382, 'eval_recall': 0.8617565970854667, 'eval_f1': 0.8506998444790046, 'eval_accuracy': 0.9916486929514279, 'eval_runtime': 16.4037, 'eval_samples_per_second': 448.314, 'eval_steps_per_second': 56.085, 'epoch': 10.0}
+{'train_runtime': 1413.3317, 'train_samples_per_second': 231.191, 'train_steps_per_second': 3.616, 'train_loss': 0.009731636565258824, 'epoch': 10.0}
+