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keles
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clef1eng

Text Classification
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xlm-roberta
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  1. README.md +71 -0
  2. config.json +29 -0
  3. model.safetensors +3 -0
  4. runs/May06_13-19-45_fa6c4cc5d275/events.out.tfevents.1715001586.fa6c4cc5d275.1360.0 +3 -0
  5. runs/May06_13-19-45_fa6c4cc5d275/events.out.tfevents.1715003253.fa6c4cc5d275.1360.1 +3 -0
  6. runs/May06_13-48-57_fa6c4cc5d275/events.out.tfevents.1715003338.fa6c4cc5d275.9491.0 +3 -0
  7. runs/May06_13-48-57_fa6c4cc5d275/events.out.tfevents.1715009342.fa6c4cc5d275.9491.1 +3 -0
  8. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ license: mit
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+ base_model: FacebookAI/xlm-roberta-large
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - f1
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+ model-index:
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+ - name: clef1eng
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # clef1eng
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+
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+ This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3082
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+ - F1: 0.7683
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 3e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 5
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 |
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+ |:-------------:|:------:|:----:|:---------------:|:------:|
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+ | 0.417 | 0.3949 | 500 | 0.3184 | 0.7343 |
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+ | 0.3081 | 0.7899 | 1000 | 0.3171 | 0.7185 |
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+ | 0.2713 | 1.1848 | 1500 | 0.3191 | 0.7559 |
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+ | 0.2528 | 1.5798 | 2000 | 0.3118 | 0.7552 |
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+ | 0.2489 | 1.9747 | 2500 | 0.3082 | 0.7683 |
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+ | 0.2225 | 2.3697 | 3000 | 0.3392 | 0.7706 |
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+ | 0.2181 | 2.7646 | 3500 | 0.3100 | 0.7616 |
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+ | 0.2088 | 3.1596 | 4000 | 0.3271 | 0.7649 |
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+ | 0.2149 | 3.5545 | 4500 | 0.3486 | 0.7644 |
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+ | 0.2126 | 3.9494 | 5000 | 0.3419 | 0.7711 |
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+ | 0.2145 | 4.3444 | 5500 | 0.3319 | 0.7651 |
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+ | 0.204 | 4.7393 | 6000 | 0.3373 | 0.7723 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.1
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
config.json ADDED
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+ {
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+ "_name_or_path": "FacebookAI/xlm-roberta-large",
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+ "architectures": [
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+ "XLMRobertaForSequenceClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "bos_token_id": 0,
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+ "classifier_dropout": null,
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+ "eos_token_id": 2,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 1024,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 4096,
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+ "layer_norm_eps": 1e-05,
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+ "max_position_embeddings": 514,
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+ "model_type": "xlm-roberta",
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+ "num_attention_heads": 16,
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+ "num_hidden_layers": 24,
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+ "output_past": true,
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+ "pad_token_id": 1,
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+ "position_embedding_type": "absolute",
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+ "problem_type": "single_label_classification",
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+ "torch_dtype": "bfloat16",
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+ "transformers_version": "4.40.1",
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+ "type_vocab_size": 1,
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+ "use_cache": true,
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+ "vocab_size": 250002
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+ }
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