Training complete

README.md

@@ -1,13 +1,7 @@
 ---
-library_name: peft
+base_model: dmis-lab/biobert-v1.1
 tags:
 - generated_from_trainer
-metrics:
-- precision
-- recall
-- f1
-- accuracy
-base_model: dmis-lab/biobert-v1.1
 model-index:
 - name: cer_model
   results: []
@@ -20,11 +14,16 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [dmis-lab/biobert-v1.1](https://huggingface.co/dmis-lab/biobert-v1.1) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.5164
-- Precision: 0.0
-- Recall: 0.0
-- F1: 0.0
-- Accuracy: 0.9993
+- eval_loss: 0.0011
+- eval_precision: 0.0
+- eval_recall: 0.0
+- eval_f1: 0.0
+- eval_accuracy: 0.9999
+- eval_runtime: 169.5558
+- eval_samples_per_second: 1.103
+- eval_steps_per_second: 0.142
+- epoch: 2.0
+- step: 282
 
 ## Model description
 
@@ -49,19 +48,11 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 1
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1  | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
-| 0.535         | 1.0   | 141  | 0.5164          | 0.0       | 0.0    | 0.0 | 0.9993   |
-
+- num_epochs: 3
 
 ### Framework versions
 
-- PEFT 0.8.2
 - Transformers 4.37.0
 - Pytorch 2.1.2+cpu
 - Datasets 2.1.0
-- Tokenizers 0.15.1
+- Tokenizers 0.15.1

config.json

@@ -0,0 +1,36 @@
+{
+  "_name_or_path": "dmis-lab/biobert-v1.1",
+  "architectures": [
+    "BertForTokenClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "O",
+    "1": "B-clinical_entity",
+    "2": "I-clinical_entity"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "B-clinical_entity": 1,
+    "I-clinical_entity": 2,
+    "O": 0
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.37.0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 28996
+}

model.safetensors

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runs/Feb11_11-26-09_dd657e7b3a39/events.out.tfevents.1707650770.dd657e7b3a39.33.0

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runs/Feb11_12-29-59_dd657e7b3a39/events.out.tfevents.1707654605.dd657e7b3a39.33.1

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training_args.bin

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