Back to all models
question-answering mask_token: [MASK]
Context
Query this model
馃敟 This model is currently loaded and running on the Inference API. 鈿狅笍 This model could not be loaded by the inference API. 鈿狅笍 This model can be loaded on the Inference API on-demand.
JSON Output
API endpoint  

鈿★笍 Upgrade your account to access the Inference API

							$
							curl -X POST \
-H "Authorization: Bearer YOUR_ORG_OR_USER_API_TOKEN" \
-H "Content-Type: application/json" \
-d '{"question": "Where does she live?", "context": "She lives in Berlin."}' \
https://api-inference.huggingface.co/models/ahotrod/electra_large_discriminator_squad2_512
Share Copied link to clipboard

Monthly model downloads

ahotrod/electra_large_discriminator_squad2_512 ahotrod/electra_large_discriminator_squad2_512
6,234 downloads
last 30 days

pytorch

tf

Contributed by

ahotrod DNeff
4 models

How to use this model directly from the 馃/transformers library:

			
Copy to clipboard
from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("ahotrod/electra_large_discriminator_squad2_512") model = AutoModelForQuestionAnswering.from_pretrained("ahotrod/electra_large_discriminator_squad2_512")

ELECTRA_large_discriminator language model fine-tuned on SQuAD2.0

with the following results:

  "exact": 87.09677419354838,
  "f1": 89.98343832723452,
  "total": 11873,
  "HasAns_exact": 84.66599190283401,
  "HasAns_f1": 90.44759839056285,
  "HasAns_total": 5928,
  "NoAns_exact": 89.52060555088309,
  "NoAns_f1": 89.52060555088309,
  "NoAns_total": 5945,
  "best_exact": 87.09677419354838,
  "best_exact_thresh": 0.0,
  "best_f1": 89.98343832723432,
  "best_f1_thresh": 0.0

from script:

python ${EXAMPLES}/run_squad.py \
  --model_type electra \
  --model_name_or_path google/electra-large-discriminator \
  --do_train \
  --do_eval \
  --train_file ${SQUAD}/train-v2.0.json \
  --predict_file ${SQUAD}/dev-v2.0.json \
  --version_2_with_negative \
  --do_lower_case \
  --num_train_epochs 3 \
  --warmup_steps 306 \
  --weight_decay 0.01 \
  --learning_rate 3e-5 \
  --max_grad_norm 0.5 \
  --adam_epsilon 1e-6 \
  --max_seq_length 512 \
  --doc_stride 128 \
  --per_gpu_train_batch_size 8 \
  --gradient_accumulation_steps 16 \
  --per_gpu_eval_batch_size 128 \
  --fp16 \
  --fp16_opt_level O1 \
  --threads 12 \
  --logging_steps 50 \
  --save_steps 1000 \
  --overwrite_output_dir \
  --output_dir ${MODEL_PATH}

using the following system & software:

Transformers: 2.11.0
PyTorch: 1.5.0
TensorFlow: 2.2.0
Python: 3.8.1
OS/Platform: Linux-5.3.0-59-generic-x86_64-with-glibc2.10
CPU/GPU: Intel i9-9900K / NVIDIA Titan RTX 24GB