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EXP_NAME: "eurlex4k_baseline_128_newds"
EXP_DESC: "Eurlex4K Baseline with len=128 on new dataset"
# Ideally would contain all the possible keys
DATA:
task_name: eurlex4k
dataset_name: eurlex
dataset_config_name: null
max_seq_length: 128
overwrite_output_dir: true
overwrite_cache: true
pad_to_max_length: true
load_from_local: true
max_train_samples: null
max_eval_samples: null
max_predict_samples: null
train_file: datasets/eurlex_raw_text_dataset/train.jsonl
validation_file: datasets/eurlex_raw_text_dataset/test.jsonl
test_file: datasets/eurlex_raw_text_dataset/test.jsonl
MODEL:
model_name_or_path: bert-base-uncased
config_name: null
tokenizer_name: null
cache_dir: null
use_fast_tokenizer: true
model_revision: main
use_auth_token: false
ignore_mismatched_sizes: false
negative_sampling: "none"
semsup: false
encoder_model_type: bert
user_custom_optimizer: null
TRAINING:
do_train: true
do_eval: true
per_device_train_batch_size: 8
gradient_accumulation_steps: 1
learning_rate: 1.e-4 # Will point to input encoder lr, if user_custom_optimizer is False
num_train_epochs: 30
save_steps: 20000
evaluation_strategy: steps
eval_steps: 10000
fp16: true
fp16_opt_level: O1
lr_scheduler_type: "constant_with_warmup" # defaults to 'linear'
dataloader_num_workers: 4
label_names: [labels]
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