metadata

tags:
  - generated_from_trainer
datasets:
  - squad_v2
model-index:
  - name: roberta-finetuned-squad_v2
    results:
      - task:
          type: question-answering
          name: Question Answering
        dataset:
          name: SQuAD v2
          type: squad_v2
          split: validation
        metrics:
          - type: exact
            value: 100
            name: Exact
          - type: f1
            value: 100
            name: F1
          - type: total
            value: 2
            name: Total

roberta-finetuned-squad_v2

This model was trained from scratch on the squad_v2 dataset. It achieves the following results on the evaluation set:

Loss: 0.8582

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 2e-05
train_batch_size: 128
eval_batch_size: 128
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 512
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss
2.9129	0.2	100	1.4700
1.4395	0.39	200	1.2407
1.2356	0.59	300	1.0325
1.1284	0.78	400	0.9750
1.0821	0.98	500	0.9345
0.9978	1.18	600	0.9893
0.9697	1.37	700	0.9300
0.9455	1.57	800	0.9351
0.9322	1.76	900	0.9451
0.9269	1.96	1000	0.9064
0.9105	2.16	1100	0.8837
0.8805	2.35	1200	0.8876
0.8703	2.55	1300	0.9853
0.8699	2.75	1400	0.9235
0.8633	2.94	1500	0.8930
0.828	3.14	1600	0.8582
0.8284	3.33	1700	0.9203
0.8076	3.53	1800	0.8866
0.7805	3.73	1900	0.9099
0.7974	3.92	2000	0.8746

Framework versions

Transformers 4.34.1
Pytorch 2.1.0+cu118
Datasets 2.14.5
Tokenizers 0.14.1