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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- squad_v2 |
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model-index: |
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- name: distilbert-finetuned-uncased-squad_v2 |
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results: |
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- task: |
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type: question-answering |
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name: Question Answering |
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dataset: |
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name: SQuAD v2 |
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type: squad_v2 |
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split: validation |
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metrics: |
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- type: exact |
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value: 100.0 |
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name: Exact |
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- type: f1 |
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value: 100.0 |
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name: F1 |
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- type: total |
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value: 2 |
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name: Total |
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- type: HasAns_exact |
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value: 100.0 |
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name: Hasans_exact |
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- type: HasAns_f1 |
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value: 100.0 |
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name: Hasans_f1 |
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- type: HasAns_total |
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value: 2 |
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name: Hasans_total |
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- type: best_exact |
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value: 100.0 |
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name: Best_exact |
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- type: best_exact_thresh |
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value: 0.7474104762077332 |
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name: Best_exact_thresh |
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- type: best_f1 |
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value: 100.0 |
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name: Best_f1 |
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- type: best_f1_thresh |
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value: 0.7474104762077332 |
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name: Best_f1_thresh |
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- type: total_time_in_seconds |
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value: 0.022410528003092622 |
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name: Total_time_in_seconds |
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- type: samples_per_second |
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value: 89.24376970163321 |
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name: Samples_per_second |
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- type: latency_in_seconds |
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value: 0.011205264001546311 |
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name: Latency_in_seconds |
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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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# distilbert-finetuned-uncased-squad_v2 |
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This model was trained from scratch on the squad_v2 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3332 |
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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: 128 |
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- eval_batch_size: 128 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 512 |
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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: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 3.6437 | 0.39 | 100 | 2.1780 | |
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| 2.1596 | 0.78 | 200 | 1.6557 | |
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| 1.8138 | 1.18 | 300 | 1.5683 | |
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| 1.6987 | 1.57 | 400 | 1.5076 | |
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| 1.6586 | 1.96 | 500 | 1.5350 | |
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| 1.5957 | 1.18 | 600 | 1.4431 | |
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| 1.5825 | 1.37 | 700 | 1.4955 | |
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| 1.5523 | 1.57 | 800 | 1.4444 | |
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| 1.5346 | 1.76 | 900 | 1.3930 | |
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| 1.5098 | 1.96 | 1000 | 1.4285 | |
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| 1.4632 | 2.16 | 1100 | 1.3630 | |
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| 1.4468 | 2.35 | 1200 | 1.3710 | |
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| 1.4343 | 2.55 | 1300 | 1.3422 | |
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| 1.4225 | 2.75 | 1400 | 1.3971 | |
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| 1.408 | 2.94 | 1500 | 1.4355 | |
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| 1.3609 | 3.14 | 1600 | 1.3332 | |
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| 1.3398 | 3.33 | 1700 | 1.3792 | |
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| 1.3224 | 3.53 | 1800 | 1.4172 | |
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| 1.3152 | 3.73 | 1900 | 1.3956 | |
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| 1.3141 | 3.92 | 2000 | 1.3748 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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