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End of training

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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: funnel-transformer/xlarge-base
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: funnel-test-512
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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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+ # funnel-test-512
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+
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+ This model is a fine-tuned version of [funnel-transformer/xlarge-base](https://huggingface.co/funnel-transformer/xlarge-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4556
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+ - Accuracy: 0.8041
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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: 1e-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: 1
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.6108 | 0.2 | 59 | 0.6724 | 0.6460 |
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+ | 0.651 | 0.4 | 118 | 0.6463 | 0.6451 |
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+ | 0.6052 | 0.61 | 177 | 0.6210 | 0.6424 |
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+ | 0.4588 | 0.81 | 236 | 0.4556 | 0.8041 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.36.2
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+ - Pytorch 2.0.1
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.0
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+ "_name_or_path": "funnel-transformer/xlarge-base",
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+ "activation_dropout": 0.0,
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+ "architectures": [
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+ "FunnelForSequenceClassification"
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+ ],
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+ "block_sizes": [
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+ "d_head": 64,
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+ "hidden_act": "gelu_new",
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+ "hidden_dropout": 0.1,
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+ "id2label": {
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+ "0": "HUMAN",
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+ "1": "AI"
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+ },
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+ "initializer_range": 0.1,
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+ "layer_norm_eps": 1e-09,
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+ "max_position_embeddings": 512,
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+ "model_type": "funnel",
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+ "n_head": 16,
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+ "num_decoder_layers": 2,
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+ "pool_q_only": true,
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+ "pooling_type": "mean",
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+ "problem_type": "single_label_classification",
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+ "rel_attn_type": "factorized",
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+ "separate_cls": true,
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+ }
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