Training in progress epoch 0

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_keras_callback
+model-index:
+- name: silviacamplani/distilbert-base-uncased-finetuned-dapt-ner-ai_data_3labels
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information Keras had access to. You should
+probably proofread and complete it, then remove this comment. -->
+
+# silviacamplani/distilbert-base-uncased-finetuned-dapt-ner-ai_data_3labels
+
+This model is a fine-tuned version of [silviacamplani/distilbert-base-uncased-finetuned-ai_data](https://huggingface.co/silviacamplani/distilbert-base-uncased-finetuned-ai_data) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Train Loss: 1.6831
+- Validation Loss: 1.5093
+- Train Precision: 0.0031
+- Train Recall: 0.0020
+- Train F1: 0.0024
+- Train Accuracy: 0.8573
+- Epoch: 0
+
+## 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:
+- optimizer: {'inner_optimizer': {'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 1e-05, 'decay_steps': 60, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
+- training_precision: mixed_float16
+
+### Training results
+
+| Train Loss | Validation Loss | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch |
+|:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:|
+| 1.6831     | 1.5093          | 0.0031          | 0.0020       | 0.0024   | 0.8573         | 0     |
+
+
+### Framework versions
+
+- Transformers 4.20.1
+- TensorFlow 2.6.4
+- Datasets 2.1.0
+- Tokenizers 0.12.1

config.json

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+{
+  "_name_or_path": "silviacamplani/distilbert-base-uncased-finetuned-ai_data",
+  "activation": "gelu",
+  "architectures": [
+    "DistilBertForTokenClassification"
+  ],
+  "attention_dropout": 0.1,
+  "dim": 768,
+  "dropout": 0.1,
+  "hidden_dim": 3072,
+  "id2label": {
+    "0": "O",
+    "1": "B-algorithm",
+    "2": "I-algorithm",
+    "3": "B-product",
+    "4": "I-product",
+    "5": "B-task",
+    "6": "I-task"
+  },
+  "initializer_range": 0.02,
+  "label2id": {
+    "B-algorithm": 1,
+    "B-product": 3,
+    "B-task": 5,
+    "I-algorithm": 2,
+    "I-product": 4,
+    "I-task": 6,
+    "O": 0
+  },
+  "max_position_embeddings": 512,
+  "model_type": "distilbert",
+  "n_heads": 12,
+  "n_layers": 6,
+  "pad_token_id": 0,
+  "qa_dropout": 0.1,
+  "seq_classif_dropout": 0.2,
+  "sinusoidal_pos_embds": false,
+  "tie_weights_": true,
+  "transformers_version": "4.20.1",
+  "vocab_size": 30522
+}

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special_tokens_map.json

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tokenizer_config.json

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+  "tokenizer_class": "DistilBertTokenizer",
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+}