End of training

.gitattributes

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 *.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 +1,76 @@
+---
+library_name: transformers
+license: mit
+base_model: FacebookAI/xlm-roberta-large
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: duration-time-v1
+  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. -->
+
+# duration-time-v1
+
+This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6917
+- Accuracy: 0.5369
+- Precision: 0.0
+- Recall: 0.0
+- F1: 0.0
+
+## 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:
+- learning_rate: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.7028        | 1.0   | 336  | 0.6964          | 0.4631   | 0.4631    | 1.0    | 0.6330 |
+| 0.7015        | 2.0   | 672  | 0.6921          | 0.5369   | 0.0       | 0.0    | 0.0    |
+| 0.7002        | 3.0   | 1008 | 0.6936          | 0.4631   | 0.4631    | 1.0    | 0.6330 |
+| 0.699         | 4.0   | 1344 | 0.6938          | 0.4631   | 0.4631    | 1.0    | 0.6330 |
+| 0.6992        | 5.0   | 1680 | 0.6906          | 0.5369   | 0.0       | 0.0    | 0.0    |
+| 0.6972        | 6.0   | 2016 | 0.6921          | 0.5369   | 0.0       | 0.0    | 0.0    |
+| 0.6963        | 7.0   | 2352 | 0.6918          | 0.5369   | 0.0       | 0.0    | 0.0    |
+| 0.6964        | 8.0   | 2688 | 0.6924          | 0.5369   | 0.0       | 0.0    | 0.0    |
+| 0.6952        | 9.0   | 3024 | 0.6919          | 0.5369   | 0.0       | 0.0    | 0.0    |
+| 0.6964        | 10.0  | 3360 | 0.6917          | 0.5369   | 0.0       | 0.0    | 0.0    |
+
+
+### Framework versions
+
+- Transformers 4.55.0
+- Pytorch 2.7.1+cu126
+- Datasets 4.0.0
+- Tokenizers 0.21.4

config.json

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+{
+  "architectures": [
+    "XLMRobertaForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "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",
+  "torch_dtype": "float32",
+  "transformers_version": "4.55.0",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 250002
+}

model.safetensors

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special_tokens_map.json

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+  "sep_token": "</s>",
+  "unk_token": "<unk>"
+}

tokenizer.json

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tokenizer_config.json

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+  "clean_up_tokenization_spaces": false,
+  "cls_token": "<s>",
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+  "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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