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:
+- distemist-85-ner
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: output
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: distemist-85-ner
+      type: distemist-85-ner
+      config: DisTEMIST NER
+      split: validation
+      args: DisTEMIST NER
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.7898351648351648
+    - name: Recall
+      type: recall
+      value: 0.8072063640617688
+    - name: F1
+      type: f1
+      value: 0.7984262902105993
+    - name: Accuracy
+      type: accuracy
+      value: 0.9768286487154489
+---
+
+<!-- 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 distemist-85-ner dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1497
+- Precision: 0.7898
+- Recall: 0.8072
+- F1: 0.7984
+- Accuracy: 0.9768
+
+## 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 |
+|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 0.9990 | 499  | 0.0739          | 0.7271    | 0.7953 | 0.7596 | 0.9731   |
+| 0.105         | 2.0    | 999  | 0.0908          | 0.7436    | 0.7890 | 0.7656 | 0.9729   |
+| 0.0448        | 2.9990 | 1498 | 0.0930          | 0.7676    | 0.7990 | 0.7830 | 0.9744   |
+| 0.0255        | 4.0    | 1998 | 0.1052          | 0.7806    | 0.7983 | 0.7894 | 0.9757   |
+| 0.0164        | 4.9990 | 2497 | 0.1100          | 0.7756    | 0.8007 | 0.7879 | 0.9750   |
+| 0.0112        | 6.0    | 2997 | 0.1266          | 0.7869    | 0.8124 | 0.7994 | 0.9768   |
+| 0.0073        | 6.9990 | 3496 | 0.1288          | 0.7929    | 0.8009 | 0.7969 | 0.9763   |
+| 0.0054        | 8.0    | 3996 | 0.1424          | 0.8032    | 0.8049 | 0.8040 | 0.9765   |
+| 0.0038        | 8.9990 | 4495 | 0.1455          | 0.7901    | 0.8042 | 0.7971 | 0.9765   |
+| 0.0028        | 9.9900 | 4990 | 0.1497          | 0.7898    | 0.8072 | 0.7984 | 0.9768   |
+
+
+### 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.1725576279.2a66098fac87.2185.0

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train.log

@@ -1454,3 +1454,16 @@ Training completed. Do not forget to share your model on huggingface.co/models =
 [INFO|trainer.py:2632] 2024-09-05 23:07:44,060 >> Loading best model from /content/dissertation/scripts/ner/output/checkpoint-3996 (score: 0.8040201005025126).
 
                                                   
 [INFO|trainer.py:4283] 2024-09-05 23:07:44,259 >> Waiting for the current checkpoint push to be finished, this might take a couple of minutes.
+[INFO|trainer.py:3503] 2024-09-05 23:08:00,051 >> Saving model checkpoint to /content/dissertation/scripts/ner/output
+[INFO|configuration_utils.py:472] 2024-09-05 23:08:00,053 >> Configuration saved in /content/dissertation/scripts/ner/output/config.json
+[INFO|modeling_utils.py:2799] 2024-09-05 23:08:01,524 >> Model weights saved in /content/dissertation/scripts/ner/output/model.safetensors
+[INFO|tokenization_utils_base.py:2684] 2024-09-05 23:08:01,525 >> tokenizer config file saved in /content/dissertation/scripts/ner/output/tokenizer_config.json
+[INFO|tokenization_utils_base.py:2693] 2024-09-05 23:08:01,525 >> Special tokens file saved in /content/dissertation/scripts/ner/output/special_tokens_map.json
+[INFO|trainer.py:3503] 2024-09-05 23:08:01,574 >> Saving model checkpoint to /content/dissertation/scripts/ner/output
+[INFO|configuration_utils.py:472] 2024-09-05 23:08:01,576 >> Configuration saved in /content/dissertation/scripts/ner/output/config.json
+[INFO|modeling_utils.py:2799] 2024-09-05 23:08:02,935 >> Model weights saved in /content/dissertation/scripts/ner/output/model.safetensors
+[INFO|tokenization_utils_base.py:2684] 2024-09-05 23:08:02,936 >> tokenizer config file saved in /content/dissertation/scripts/ner/output/tokenizer_config.json
+[INFO|tokenization_utils_base.py:2693] 2024-09-05 23:08:02,937 >> Special tokens file saved in /content/dissertation/scripts/ner/output/special_tokens_map.json
+{'eval_loss': 0.14972682297229767, 'eval_precision': 0.7898351648351648, 'eval_recall': 0.8072063640617688, 'eval_f1': 0.7984262902105993, 'eval_accuracy': 0.9768286487154489, 'eval_runtime': 14.3927, 'eval_samples_per_second': 473.158, 'eval_steps_per_second': 59.197, 'epoch': 9.99}
+{'train_runtime': 1385.1143, 'train_samples_per_second': 230.645, 'train_steps_per_second': 3.603, 'train_loss': 0.022475468706272407, 'epoch': 9.99}
+