prajwalJumde commited on
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End of training

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+ ---
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+ license: mit
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+ base_model: xlm-roberta-base
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: QA_SYNTH_DATA_WITH_UNANSWERABLE_05_SEPT
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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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+ # QA_SYNTH_DATA_WITH_UNANSWERABLE_05_SEPT
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+
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+ This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0053
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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: 2e-05
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+ - train_batch_size: 2
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+ - eval_batch_size: 2
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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: 10
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:------:|:---------------:|
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+ | 0.0478 | 1.0 | 16275 | 0.0446 |
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+ | 0.0825 | 2.0 | 32550 | 0.0349 |
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+ | 0.0674 | 3.0 | 48825 | 0.0366 |
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+ | 0.0088 | 4.0 | 65100 | 0.0301 |
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+ | 0.0102 | 5.0 | 81375 | 0.0110 |
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+ | 0.0036 | 6.0 | 97650 | 0.0040 |
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+ | 0.0 | 7.0 | 113925 | 0.0055 |
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+ | 0.0 | 8.0 | 130200 | 0.0056 |
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+ | 0.0 | 9.0 | 146475 | 0.0052 |
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+ | 0.0 | 10.0 | 162750 | 0.0053 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.32.0.dev0
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+ - Pytorch 2.0.1+cu117
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+ - Datasets 2.14.4
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+ - Tokenizers 0.13.3
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+ "initializer_range": 0.02,
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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": 12,
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+ "num_hidden_layers": 12,
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+ "output_past": true,
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+ "position_embedding_type": "absolute",
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+ "transformers_version": "4.32.0.dev0",
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+ "use_cache": true,
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