metadata
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: fnet-base-finetuned-mnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MNLI
type: glue
args: mnli
metrics:
- name: Accuracy
type: accuracy
value: 0.7674938974776241
fnet-base-finetuned-mnli
This model is a fine-tuned version of google/fnet-base on the GLUE MNLI dataset. It achieves the following results on the evaluation set:
- Loss: 0.6443
- Accuracy: 0.7675
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
This model is trained using the run_glue script. The following command was used:
#!/usr/bin/bash
python ../run_glue.py \
--model_name_or_path google/fnet-base \
--task_name mnli \
--do_train \
--do_eval \
--max_seq_length 512 \
--per_device_train_batch_size 16 \
--learning_rate 2e-5 \
--num_train_epochs 3 \
--output_dir fnet-base-finetuned-mnli \
--push_to_hub \
--hub_strategy all_checkpoints \
--logging_strategy epoch \
--save_strategy epoch \
--evaluation_strategy epoch \
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.7143 | 1.0 | 24544 | 0.6169 | 0.7504 |
0.5407 | 2.0 | 49088 | 0.6218 | 0.7627 |
0.4178 | 3.0 | 73632 | 0.6564 | 0.7658 |
Framework versions
- Transformers 4.11.0.dev0
- Pytorch 1.9.0
- Datasets 1.12.1
- Tokenizers 0.10.3