End of training

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,73 @@
+---
+library_name: transformers
+base_model: FacebookAI/xlm-roberta-large-finetuned-conll02-dutch
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: ddd314bfb7b8f41aee216bed7b21bee2
+  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. -->
+
+# ddd314bfb7b8f41aee216bed7b21bee2
+
+This model is a fine-tuned version of [FacebookAI/xlm-roberta-large-finetuned-conll02-dutch](https://huggingface.co/FacebookAI/xlm-roberta-large-finetuned-conll02-dutch) on the contemmcm/cls_mmlu dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.3898
+- Data Size: 0.25
+- Epoch Runtime: 24.4660
+- Accuracy: 0.2487
+- F1 Macro: 0.0996
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 4
+- total_train_batch_size: 32
+- total_eval_batch_size: 32
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: constant
+- num_epochs: 50
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Data Size | Epoch Runtime | Accuracy | F1 Macro |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------------:|:--------:|:--------:|
+| No log        | 0     | 0    | 1.4378          | 0         | 3.2351        | 0.2513   | 0.1312   |
+| No log        | 1     | 438  | 1.4304          | 0.0078    | 3.8023        | 0.2527   | 0.1008   |
+| No log        | 2     | 876  | 1.3882          | 0.0156    | 4.6046        | 0.2460   | 0.0999   |
+| No log        | 3     | 1314 | 1.3912          | 0.0312    | 6.6180        | 0.2533   | 0.1011   |
+| No log        | 4     | 1752 | 1.3940          | 0.0625    | 10.0974       | 0.2487   | 0.0996   |
+| 0.0785        | 5     | 2190 | 1.3944          | 0.125     | 15.1189       | 0.2527   | 0.1008   |
+| 0.1856        | 6     | 2628 | 1.3898          | 0.25      | 24.4660       | 0.2487   | 0.0996   |
+
+
+### Framework versions
+
+- Transformers 4.57.0
+- Pytorch 2.8.0+cu128
+- Datasets 4.3.0
+- Tokenizers 0.22.1

config.json

@@ -0,0 +1,41 @@
+{
+  "_num_labels": 9,
+  "architectures": [
+    "XLMRobertaForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "dtype": "float32",
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2",
+    "3": "LABEL_3"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2,
+    "LABEL_3": 3
+  },
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "xlm-roberta",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "output_past": true,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "transformers_version": "4.57.0",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 250002
+}

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special_tokens_map.json

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+}

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tokenizer_config.json

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+  "clean_up_tokenization_spaces": false,
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "extra_special_tokens": {},
+  "mask_token": "<mask>",
+  "model_max_length": 512,
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "tokenizer_class": "XLMRobertaTokenizer",
+  "unk_token": "<unk>"
+}

training_args.bin

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