End of training

README.md

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+---
+license: mit
+base_model: DTAI-KULeuven/robbert-2023-dutch-large
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: robbert-2023-dutch-large_ner
+  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. -->
+
+# robbert-2023-dutch-large_ner
+
+This model is a fine-tuned version of [DTAI-KULeuven/robbert-2023-dutch-large](https://huggingface.co/DTAI-KULeuven/robbert-2023-dutch-large) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3927
+- Precision: 0.9137
+- Recall: 0.9190
+- F1: 0.9162
+- Accuracy: 0.9515
+
+## 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: 16
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 438  | 0.3076          | 0.8616    | 0.8592 | 0.8581 | 0.9133   |
+| 0.4231        | 2.0   | 876  | 0.2583          | 0.9068    | 0.8795 | 0.8919 | 0.9338   |
+| 0.2222        | 3.0   | 1314 | 0.2809          | 0.8821    | 0.8940 | 0.8864 | 0.9331   |
+| 0.1519        | 4.0   | 1752 | 0.2549          | 0.9142    | 0.9207 | 0.9169 | 0.9505   |
+| 0.1094        | 5.0   | 2190 | 0.2487          | 0.9105    | 0.9145 | 0.9121 | 0.9482   |
+| 0.0731        | 6.0   | 2628 | 0.3406          | 0.9094    | 0.9108 | 0.9097 | 0.9473   |
+| 0.0445        | 7.0   | 3066 | 0.3137          | 0.9118    | 0.9164 | 0.9139 | 0.9498   |
+| 0.0251        | 8.0   | 3504 | 0.3178          | 0.9166    | 0.9209 | 0.9186 | 0.9526   |
+| 0.0251        | 9.0   | 3942 | 0.3886          | 0.9118    | 0.9170 | 0.9143 | 0.9504   |
+| 0.0129        | 10.0  | 4380 | 0.3927          | 0.9137    | 0.9190 | 0.9162 | 0.9515   |
+
+
+### Framework versions
+
+- Transformers 4.42.4
+- Pytorch 2.3.1+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "DTAI-KULeuven/robbert-2023-dutch-large",
+  "additional_special_tokens_ids": [],
+  "architectures": [
+    "RobertaForTokenClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "cls_token_id": 0,
+  "eos_token_id": 1,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2",
+    "3": "LABEL_3",
+    "4": "LABEL_4",
+    "5": "LABEL_5",
+    "6": "LABEL_6"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2,
+    "LABEL_3": 3,
+    "LABEL_4": 4,
+    "LABEL_5": 5,
+    "LABEL_6": 6
+  },
+  "layer_norm_eps": 1e-05,
+  "mask_token_id": 4,
+  "max_position_embeddings": 514,
+  "model_type": "roberta",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "sep_token_id": 3,
+  "tokenizer_class": "RobertaTokenizerFast",
+  "torch_dtype": "float32",
+  "transformers_version": "4.42.4",
+  "type_vocab_size": 1,
+  "unk_token_id": 2,
+  "use_cache": true,
+  "vocab_size": 50000
+}

model.safetensors

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training_args.bin

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