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--- |
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base_model: allenai/longformer-base-4096 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- essays_su_g |
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metrics: |
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- accuracy |
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model-index: |
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- name: longformer-spans |
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results: |
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- task: |
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name: Token Classification |
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type: token-classification |
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dataset: |
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name: essays_su_g |
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type: essays_su_g |
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config: spans |
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split: train[80%:100%] |
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args: spans |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.935805061732865 |
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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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# longformer-spans |
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This model is a fine-tuned version of [allenai/longformer-base-4096](https://huggingface.co/allenai/longformer-base-4096) on the essays_su_g dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1821 |
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- B: {'precision': 0.8143972246313964, 'recall': 0.900287631831256, 'f1-score': 0.8551912568306012, 'support': 1043.0} |
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- I: {'precision': 0.9392924896774913, 'recall': 0.9702593659942363, 'f1-score': 0.9545248355636199, 'support': 17350.0} |
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- O: {'precision': 0.944873595505618, 'recall': 0.8750270973336224, 'f1-score': 0.9086100168823861, 'support': 9226.0} |
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- Accuracy: 0.9358 |
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- Macro avg: {'precision': 0.8995211032715019, 'recall': 0.9151913650530382, 'f1-score': 0.9061087030922024, 'support': 27619.0} |
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- Weighted avg: {'precision': 0.936440305345228, 'recall': 0.935805061732865, 'f1-score': 0.9354359822462803, 'support': 27619.0} |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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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: 8 |
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- eval_batch_size: 8 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | B | I | O | Accuracy | Macro avg | Weighted avg | |
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|:-------------:|:-----:|:----:|:---------------:|:-------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------:|:--------:|:-------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:| |
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| No log | 1.0 | 41 | 0.3420 | {'precision': 0.7641196013289037, 'recall': 0.22051773729626079, 'f1-score': 0.3422619047619047, 'support': 1043.0} | {'precision': 0.8498853325356466, 'recall': 0.9825360230547551, 'f1-score': 0.9114093242087253, 'support': 17350.0} | {'precision': 0.9462809917355371, 'recall': 0.7446347279427704, 'f1-score': 0.8334344292126653, 'support': 9226.0} | 0.8743 | {'precision': 0.8534286418666958, 'recall': 0.6492294960979287, 'f1-score': 0.6957018860610984, 'support': 27619.0} | {'precision': 0.8788470144984097, 'recall': 0.8742894384300662, 'f1-score': 0.8638689664942287, 'support': 27619.0} | |
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| No log | 2.0 | 82 | 0.2028 | {'precision': 0.7734241908006815, 'recall': 0.8705656759348035, 'f1-score': 0.8191249436175011, 'support': 1043.0} | {'precision': 0.9413330313154765, 'recall': 0.9580979827089338, 'f1-score': 0.9496415207518066, 'support': 17350.0} | {'precision': 0.9263601183701343, 'recall': 0.8821807934099285, 'f1-score': 0.9037308461025984, 'support': 9226.0} | 0.9294 | {'precision': 0.8803724468287641, 'recall': 0.903614817351222, 'f1-score': 0.8908324368239686, 'support': 27619.0} | {'precision': 0.9299905129226795, 'recall': 0.9294326369528223, 'f1-score': 0.9293764613990178, 'support': 27619.0} | |
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| No log | 3.0 | 123 | 0.2004 | {'precision': 0.7942905121746432, 'recall': 0.9069990412272292, 'f1-score': 0.8469113697403761, 'support': 1043.0} | {'precision': 0.9219560115701577, 'recall': 0.9736599423631124, 'f1-score': 0.9471028508956354, 'support': 17350.0} | {'precision': 0.9505243676742752, 'recall': 0.835031432907002, 'f1-score': 0.8890427557555824, 'support': 9226.0} | 0.9248 | {'precision': 0.8889236304730254, 'recall': 0.9052301388324479, 'f1-score': 0.8943523254638647, 'support': 27619.0} | {'precision': 0.9266779977951141, 'recall': 0.9248343531626778, 'f1-score': 0.9239245260972333, 'support': 27619.0} | |
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| No log | 4.0 | 164 | 0.1732 | {'precision': 0.8319928507596068, 'recall': 0.8926174496644296, 'f1-score': 0.8612395929694727, 'support': 1043.0} | {'precision': 0.9531670965892806, 'recall': 0.9583861671469741, 'f1-score': 0.9557695071130909, 'support': 17350.0} | {'precision': 0.9240198785201547, 'recall': 0.9068935616735313, 'f1-score': 0.9153766205349817, 'support': 9226.0} | 0.9387 | {'precision': 0.9030599419563474, 'recall': 0.9192990594949784, 'f1-score': 0.9107952402058485, 'support': 27619.0} | {'precision': 0.9388545953290572, 'recall': 0.9387016184510663, 'f1-score': 0.9387066347418453, 'support': 27619.0} | |
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| No log | 5.0 | 205 | 0.1821 | {'precision': 0.8143972246313964, 'recall': 0.900287631831256, 'f1-score': 0.8551912568306012, 'support': 1043.0} | {'precision': 0.9392924896774913, 'recall': 0.9702593659942363, 'f1-score': 0.9545248355636199, 'support': 17350.0} | {'precision': 0.944873595505618, 'recall': 0.8750270973336224, 'f1-score': 0.9086100168823861, 'support': 9226.0} | 0.9358 | {'precision': 0.8995211032715019, 'recall': 0.9151913650530382, 'f1-score': 0.9061087030922024, 'support': 27619.0} | {'precision': 0.936440305345228, 'recall': 0.935805061732865, 'f1-score': 0.9354359822462803, 'support': 27619.0} | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.2 |
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