/
ct_java_small_ablation_only_shortest_paths.yaml
94 lines (86 loc) · 2.02 KB
/
ct_java_small_ablation_only_shortest_paths.yaml
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experiment_setup:
executable: 'code_transformer/experiments/code_transformer/code_summarization.py'
data_setup:
language: 'java-small'
filter_language: None
use_validation: True
num_sub_tokens: 5
num_subtokens_output: 6
use_only_ast: True
mask_all_tokens: False
use_no_punctuation: True
use_pointer_network: False
sort_by_length: False
shuffle: False
chunk_size: 32
data_transforms:
max_distance_mask: None
relative_distances:
- shortest_paths
distance_binning:
type: 'exponential'
growth_factor: 1.3
n_fixed_bins: 9
transfer_learning:
use_pretrained_model: False
model_type: 'ct_code_summarization'
run_id: CT-23
snapshot_iteration: 10
cpu: False
freeze_encoder_layers: None
model:
with_cuda: True
label_smoothing: 0.1
lm_encoder:
input_nonlinearity: 'tanh'
num_languages: None
transformer:
num_layers: 3
encoder_layer:
d_model: 1024
nhead: 8
dim_feedforward: 2048
dropout: 0.2
activation: 'gelu'
use_content_content: True
use_content_pos: True
use_pos_content: True
use_pos_pos: True
use_token_distances: False
lm_decoder:
output_nonlinearity: None
n_layers: 1
decoder_dropout: 0
decoder_nhead: 8
decoder_dim_feedforward: 2048
decoder_activation: 'gelu'
use_teacher_forcing: True
pointer_attention_type: 'additive'
use_pointer_query_linear: False
use_pointer_query_self_attention: False
concat_query_and_pointer: True
attend_cls_token: True
optimizer:
optimizer: 'Adam'
learning_rate: 8e-5
reg_scale: 3e-5
training:
random_seed: 456
batch_size: 8
simulated_batch_size: 128
simulated_batch_size_valid: 1280
accumulate_tokens_batch: False
validate_every: 100
persistent_snapshot_every: 10000
early_stopping_patience: 20
max_validation_samples: 50000
metrics:
- top1_accuracy
- top5_accuracy
- non_trivial_accuracy
- precision
- recall
- f1_score
- micro_f1_score
- rouge_2
- rouge_l