upload model weights after 2400 training steps with frozen pretrained weights, this performs worse than checkpoint 1000 on test set T_T
Browse files- codebert-base-cross-entropy/checkpoint-2000/config.json +27 -0
- codebert-base-cross-entropy/checkpoint-2000/merges.txt +0 -0
- codebert-base-cross-entropy/checkpoint-2000/model.safetensors +3 -0
- codebert-base-cross-entropy/checkpoint-2000/optimizer.pt +3 -0
- codebert-base-cross-entropy/checkpoint-2000/rng_state.pth +3 -0
- codebert-base-cross-entropy/checkpoint-2000/scaler.pt +3 -0
- codebert-base-cross-entropy/checkpoint-2000/scheduler.pt +3 -0
- codebert-base-cross-entropy/checkpoint-2000/special_tokens_map.json +51 -0
- codebert-base-cross-entropy/checkpoint-2000/tokenizer.json +0 -0
- codebert-base-cross-entropy/checkpoint-2000/tokenizer_config.json +58 -0
- codebert-base-cross-entropy/checkpoint-2000/trainer_state.json +1539 -0
- codebert-base-cross-entropy/checkpoint-2000/training_args.bin +3 -0
- codebert-base-cross-entropy/checkpoint-2000/vocab.json +0 -0
- codebert-base-cross-entropy/checkpoint-2400/config.json +27 -0
- codebert-base-cross-entropy/checkpoint-2400/merges.txt +0 -0
- codebert-base-cross-entropy/checkpoint-2400/model.safetensors +3 -0
- codebert-base-cross-entropy/checkpoint-2400/optimizer.pt +3 -0
- codebert-base-cross-entropy/checkpoint-2400/rng_state.pth +3 -0
- codebert-base-cross-entropy/checkpoint-2400/scaler.pt +3 -0
- codebert-base-cross-entropy/checkpoint-2400/scheduler.pt +3 -0
- codebert-base-cross-entropy/checkpoint-2400/special_tokens_map.json +51 -0
- codebert-base-cross-entropy/checkpoint-2400/tokenizer.json +0 -0
- codebert-base-cross-entropy/checkpoint-2400/tokenizer_config.json +58 -0
- codebert-base-cross-entropy/checkpoint-2400/trainer_state.json +1819 -0
- codebert-base-cross-entropy/checkpoint-2400/training_args.bin +3 -0
- codebert-base-cross-entropy/checkpoint-2400/vocab.json +0 -0
- codebert-base-cross-entropy/training.log +324 -0
codebert-base-cross-entropy/checkpoint-2000/config.json
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{
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"architectures": [
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"RobertaForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"bos_token_id": 0,
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"dtype": "float32",
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 514,
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"model_type": "roberta",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"output_past": true,
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"pad_token_id": 1,
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"position_embedding_type": "absolute",
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"transformers_version": "4.56.0",
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 50265
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}
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codebert-base-cross-entropy/checkpoint-2000/merges.txt
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codebert-base-cross-entropy/checkpoint-2000/model.safetensors
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size 498612824
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codebert-base-cross-entropy/checkpoint-2000/optimizer.pt
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version https://git-lfs.github.com/spec/v1
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size 4741859
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codebert-base-cross-entropy/checkpoint-2000/rng_state.pth
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size 14645
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codebert-base-cross-entropy/checkpoint-2000/scaler.pt
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version https://git-lfs.github.com/spec/v1
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size 1383
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codebert-base-cross-entropy/checkpoint-2000/scheduler.pt
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version https://git-lfs.github.com/spec/v1
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size 1465
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codebert-base-cross-entropy/checkpoint-2000/special_tokens_map.json
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{
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"bos_token": {
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"content": "<s>",
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"lstrip": false,
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"normalized": true,
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"mask_token": {
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"content": "<mask>",
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"lstrip": true,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": {
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"content": "<pad>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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"sep_token": {
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"content": "</s>",
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"lstrip": false,
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"unk_token": {
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"single_word": false
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}
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}
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codebert-base-cross-entropy/checkpoint-2000/tokenizer.json
ADDED
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codebert-base-cross-entropy/checkpoint-2000/tokenizer_config.json
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|
| 11 |
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|
| 19 |
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"2": {
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| 27 |
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"3": {
|
| 29 |
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| 30 |
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| 31 |
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| 32 |
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"rstrip": false,
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| 33 |
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"single_word": false,
|
| 34 |
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"special": true
|
| 35 |
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},
|
| 36 |
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"50264": {
|
| 37 |
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"content": "<mask>",
|
| 38 |
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"lstrip": true,
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| 39 |
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"normalized": false,
|
| 40 |
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| 41 |
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|
| 42 |
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"special": true
|
| 43 |
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}
|
| 44 |
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},
|
| 45 |
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"bos_token": "<s>",
|
| 46 |
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"clean_up_tokenization_spaces": false,
|
| 47 |
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"cls_token": "<s>",
|
| 48 |
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"eos_token": "</s>",
|
| 49 |
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"errors": "replace",
|
| 50 |
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"extra_special_tokens": {},
|
| 51 |
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"mask_token": "<mask>",
|
| 52 |
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"model_max_length": 512,
|
| 53 |
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"pad_token": "<pad>",
|
| 54 |
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"sep_token": "</s>",
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| 55 |
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"tokenizer_class": "RobertaTokenizer",
|
| 56 |
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"trim_offsets": true,
|
| 57 |
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"unk_token": "<unk>"
|
| 58 |
+
}
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codebert-base-cross-entropy/checkpoint-2000/trainer_state.json
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| 30 |
+
"pad_token": {
|
| 31 |
+
"content": "<pad>",
|
| 32 |
+
"lstrip": false,
|
| 33 |
+
"normalized": true,
|
| 34 |
+
"rstrip": false,
|
| 35 |
+
"single_word": false
|
| 36 |
+
},
|
| 37 |
+
"sep_token": {
|
| 38 |
+
"content": "</s>",
|
| 39 |
+
"lstrip": false,
|
| 40 |
+
"normalized": true,
|
| 41 |
+
"rstrip": false,
|
| 42 |
+
"single_word": false
|
| 43 |
+
},
|
| 44 |
+
"unk_token": {
|
| 45 |
+
"content": "<unk>",
|
| 46 |
+
"lstrip": false,
|
| 47 |
+
"normalized": true,
|
| 48 |
+
"rstrip": false,
|
| 49 |
+
"single_word": false
|
| 50 |
+
}
|
| 51 |
+
}
|
codebert-base-cross-entropy/checkpoint-2400/tokenizer.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
codebert-base-cross-entropy/checkpoint-2400/tokenizer_config.json
ADDED
|
@@ -0,0 +1,58 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 3 |
+
"added_tokens_decoder": {
|
| 4 |
+
"0": {
|
| 5 |
+
"content": "<s>",
|
| 6 |
+
"lstrip": false,
|
| 7 |
+
"normalized": true,
|
| 8 |
+
"rstrip": false,
|
| 9 |
+
"single_word": false,
|
| 10 |
+
"special": true
|
| 11 |
+
},
|
| 12 |
+
"1": {
|
| 13 |
+
"content": "<pad>",
|
| 14 |
+
"lstrip": false,
|
| 15 |
+
"normalized": true,
|
| 16 |
+
"rstrip": false,
|
| 17 |
+
"single_word": false,
|
| 18 |
+
"special": true
|
| 19 |
+
},
|
| 20 |
+
"2": {
|
| 21 |
+
"content": "</s>",
|
| 22 |
+
"lstrip": false,
|
| 23 |
+
"normalized": true,
|
| 24 |
+
"rstrip": false,
|
| 25 |
+
"single_word": false,
|
| 26 |
+
"special": true
|
| 27 |
+
},
|
| 28 |
+
"3": {
|
| 29 |
+
"content": "<unk>",
|
| 30 |
+
"lstrip": false,
|
| 31 |
+
"normalized": true,
|
| 32 |
+
"rstrip": false,
|
| 33 |
+
"single_word": false,
|
| 34 |
+
"special": true
|
| 35 |
+
},
|
| 36 |
+
"50264": {
|
| 37 |
+
"content": "<mask>",
|
| 38 |
+
"lstrip": true,
|
| 39 |
+
"normalized": false,
|
| 40 |
+
"rstrip": false,
|
| 41 |
+
"single_word": false,
|
| 42 |
+
"special": true
|
| 43 |
+
}
|
| 44 |
+
},
|
| 45 |
+
"bos_token": "<s>",
|
| 46 |
+
"clean_up_tokenization_spaces": false,
|
| 47 |
+
"cls_token": "<s>",
|
| 48 |
+
"eos_token": "</s>",
|
| 49 |
+
"errors": "replace",
|
| 50 |
+
"extra_special_tokens": {},
|
| 51 |
+
"mask_token": "<mask>",
|
| 52 |
+
"model_max_length": 512,
|
| 53 |
+
"pad_token": "<pad>",
|
| 54 |
+
"sep_token": "</s>",
|
| 55 |
+
"tokenizer_class": "RobertaTokenizer",
|
| 56 |
+
"trim_offsets": true,
|
| 57 |
+
"unk_token": "<unk>"
|
| 58 |
+
}
|
codebert-base-cross-entropy/checkpoint-2400/trainer_state.json
ADDED
|
@@ -0,0 +1,1819 @@
|
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|
| 1 |
+
2026-04-15 11:40:23,361 - INFO - train_pipeline - Logging to ./output_checkpoints/codebert-base-cross-entropy/training.log
|
| 2 |
+
2026-04-15 11:40:23,369 - INFO - train_pipeline - Loading model & tokenizer for 'microsoft/codebert-base'
|
| 3 |
+
2026-04-15 11:40:25,679 - INFO - train_pipeline - Model placed on cuda
|
| 4 |
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2026-04-15 11:40:25,694 - INFO - train_pipeline - ===== Model Architecture =====
|
| 5 |
+
2026-04-15 11:40:25,708 - INFO - train_pipeline -
|
| 6 |
+
RobertaForSequenceClassification(
|
| 7 |
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(roberta): RobertaModel(
|
| 8 |
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(embeddings): RobertaEmbeddings(
|
| 9 |
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(word_embeddings): Embedding(50265, 768, padding_idx=1)
|
| 10 |
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(position_embeddings): Embedding(514, 768, padding_idx=1)
|
| 11 |
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(token_type_embeddings): Embedding(1, 768)
|
| 12 |
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(LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
|
| 13 |
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(dropout): Dropout(p=0.1, inplace=False)
|
| 14 |
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)
|
| 15 |
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(encoder): RobertaEncoder(
|
| 16 |
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(layer): ModuleList(
|
| 17 |
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(0-11): 12 x RobertaLayer(
|
| 18 |
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(attention): RobertaAttention(
|
| 19 |
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(self): RobertaSdpaSelfAttention(
|
| 20 |
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(query): Linear(in_features=768, out_features=768, bias=True)
|
| 21 |
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(key): Linear(in_features=768, out_features=768, bias=True)
|
| 22 |
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(value): Linear(in_features=768, out_features=768, bias=True)
|
| 23 |
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(dropout): Dropout(p=0.1, inplace=False)
|
| 24 |
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)
|
| 25 |
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(output): RobertaSelfOutput(
|
| 26 |
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(dense): Linear(in_features=768, out_features=768, bias=True)
|
| 27 |
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(LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
|
| 28 |
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(dropout): Dropout(p=0.1, inplace=False)
|
| 29 |
+
)
|
| 30 |
+
)
|
| 31 |
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(intermediate): RobertaIntermediate(
|
| 32 |
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(dense): Linear(in_features=768, out_features=3072, bias=True)
|
| 33 |
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(intermediate_act_fn): GELUActivation()
|
| 34 |
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)
|
| 35 |
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(output): RobertaOutput(
|
| 36 |
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(dense): Linear(in_features=3072, out_features=768, bias=True)
|
| 37 |
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(LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
|
| 38 |
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(dropout): Dropout(p=0.1, inplace=False)
|
| 39 |
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)
|
| 40 |
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|
| 41 |
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|
| 42 |
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|
| 43 |
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|
| 44 |
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(classifier): RobertaClassificationHead(
|
| 45 |
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(dense): Linear(in_features=768, out_features=768, bias=True)
|
| 46 |
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(dropout): Dropout(p=0.1, inplace=False)
|
| 47 |
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(out_proj): Linear(in_features=768, out_features=2, bias=True)
|
| 48 |
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)
|
| 49 |
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)
|
| 50 |
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2026-04-15 11:40:25,734 - INFO - train_pipeline - ===== Tokenizer Summary =====
|
| 51 |
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2026-04-15 11:40:25,811 - INFO - train_pipeline - Vocab size: 50265 | Special tokens: ['<s>', '</s>', '<unk>', '<pad>', '<mask>']
|
| 52 |
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2026-04-15 11:40:25,830 - INFO - train_pipeline - ===== End of Architecture Log =====
|
| 53 |
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2026-04-15 11:40:25,852 - INFO - train_pipeline - Base model weights frozen – only classifier head will be trained.
|
| 54 |
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2026-04-15 11:40:27,878 - INFO - train_pipeline - === Starting training ===
|
| 55 |
+
2026-04-15 11:40:23,361 - INFO - train_pipeline - Logging to ./output_checkpoints/codebert-base-cross-entropy/training.log
|
| 56 |
+
2026-04-15 11:40:23,369 - INFO - train_pipeline - Loading model & tokenizer for 'microsoft/codebert-base'
|
| 57 |
+
2026-04-15 11:40:25,679 - INFO - train_pipeline - Model placed on cuda
|
| 58 |
+
2026-04-15 11:40:25,694 - INFO - train_pipeline - ===== Model Architecture =====
|
| 59 |
+
2026-04-15 11:40:25,708 - INFO - train_pipeline -
|
| 60 |
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RobertaForSequenceClassification(
|
| 61 |
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(roberta): RobertaModel(
|
| 62 |
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(embeddings): RobertaEmbeddings(
|
| 63 |
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(word_embeddings): Embedding(50265, 768, padding_idx=1)
|
| 64 |
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(position_embeddings): Embedding(514, 768, padding_idx=1)
|
| 65 |
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(token_type_embeddings): Embedding(1, 768)
|
| 66 |
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(LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
|
| 67 |
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(dropout): Dropout(p=0.1, inplace=False)
|
| 68 |
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)
|
| 69 |
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(encoder): RobertaEncoder(
|
| 70 |
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(layer): ModuleList(
|
| 71 |
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(0-11): 12 x RobertaLayer(
|
| 72 |
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(attention): RobertaAttention(
|
| 73 |
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(self): RobertaSdpaSelfAttention(
|
| 74 |
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(query): Linear(in_features=768, out_features=768, bias=True)
|
| 75 |
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(key): Linear(in_features=768, out_features=768, bias=True)
|
| 76 |
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(value): Linear(in_features=768, out_features=768, bias=True)
|
| 77 |
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|
| 78 |
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)
|
| 79 |
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(output): RobertaSelfOutput(
|
| 80 |
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(dense): Linear(in_features=768, out_features=768, bias=True)
|
| 81 |
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(LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
|
| 82 |
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(dropout): Dropout(p=0.1, inplace=False)
|
| 83 |
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)
|
| 84 |
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)
|
| 85 |
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(intermediate): RobertaIntermediate(
|
| 86 |
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(dense): Linear(in_features=768, out_features=3072, bias=True)
|
| 87 |
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(intermediate_act_fn): GELUActivation()
|
| 88 |
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)
|
| 89 |
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(output): RobertaOutput(
|
| 90 |
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(dense): Linear(in_features=3072, out_features=768, bias=True)
|
| 91 |
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(LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
|
| 92 |
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(dropout): Dropout(p=0.1, inplace=False)
|
| 93 |
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|
| 94 |
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|
| 95 |
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|
| 96 |
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|
| 97 |
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)
|
| 98 |
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(classifier): RobertaClassificationHead(
|
| 99 |
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(dense): Linear(in_features=768, out_features=768, bias=True)
|
| 100 |
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(dropout): Dropout(p=0.1, inplace=False)
|
| 101 |
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(out_proj): Linear(in_features=768, out_features=2, bias=True)
|
| 102 |
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)
|
| 103 |
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|
| 104 |
+
2026-04-15 11:40:25,734 - INFO - train_pipeline - ===== Tokenizer Summary =====
|
| 105 |
+
2026-04-15 11:40:25,811 - INFO - train_pipeline - Vocab size: 50265 | Special tokens: ['<s>', '</s>', '<unk>', '<pad>', '<mask>']
|
| 106 |
+
2026-04-15 11:40:25,830 - INFO - train_pipeline - ===== End of Architecture Log =====
|
| 107 |
+
2026-04-15 11:40:25,852 - INFO - train_pipeline - Base model weights frozen – only classifier head will be trained.
|
| 108 |
+
2026-04-15 11:40:27,878 - INFO - train_pipeline - === Starting training ===
|
| 109 |
+
2026-04-15 11:40:23,361 - INFO - train_pipeline - Logging to ./output_checkpoints/codebert-base-cross-entropy/training.log
|
| 110 |
+
2026-04-15 11:40:23,369 - INFO - train_pipeline - Loading model & tokenizer for 'microsoft/codebert-base'
|
| 111 |
+
2026-04-15 11:40:25,679 - INFO - train_pipeline - Model placed on cuda
|
| 112 |
+
2026-04-15 11:40:25,694 - INFO - train_pipeline - ===== Model Architecture =====
|
| 113 |
+
2026-04-15 11:40:25,708 - INFO - train_pipeline -
|
| 114 |
+
RobertaForSequenceClassification(
|
| 115 |
+
(roberta): RobertaModel(
|
| 116 |
+
(embeddings): RobertaEmbeddings(
|
| 117 |
+
(word_embeddings): Embedding(50265, 768, padding_idx=1)
|
| 118 |
+
(position_embeddings): Embedding(514, 768, padding_idx=1)
|
| 119 |
+
(token_type_embeddings): Embedding(1, 768)
|
| 120 |
+
(LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
|
| 121 |
+
(dropout): Dropout(p=0.1, inplace=False)
|
| 122 |
+
)
|
| 123 |
+
(encoder): RobertaEncoder(
|
| 124 |
+
(layer): ModuleList(
|
| 125 |
+
(0-11): 12 x RobertaLayer(
|
| 126 |
+
(attention): RobertaAttention(
|
| 127 |
+
(self): RobertaSdpaSelfAttention(
|
| 128 |
+
(query): Linear(in_features=768, out_features=768, bias=True)
|
| 129 |
+
(key): Linear(in_features=768, out_features=768, bias=True)
|
| 130 |
+
(value): Linear(in_features=768, out_features=768, bias=True)
|
| 131 |
+
(dropout): Dropout(p=0.1, inplace=False)
|
| 132 |
+
)
|
| 133 |
+
(output): RobertaSelfOutput(
|
| 134 |
+
(dense): Linear(in_features=768, out_features=768, bias=True)
|
| 135 |
+
(LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
|
| 136 |
+
(dropout): Dropout(p=0.1, inplace=False)
|
| 137 |
+
)
|
| 138 |
+
)
|
| 139 |
+
(intermediate): RobertaIntermediate(
|
| 140 |
+
(dense): Linear(in_features=768, out_features=3072, bias=True)
|
| 141 |
+
(intermediate_act_fn): GELUActivation()
|
| 142 |
+
)
|
| 143 |
+
(output): RobertaOutput(
|
| 144 |
+
(dense): Linear(in_features=3072, out_features=768, bias=True)
|
| 145 |
+
(LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
|
| 146 |
+
(dropout): Dropout(p=0.1, inplace=False)
|
| 147 |
+
)
|
| 148 |
+
)
|
| 149 |
+
)
|
| 150 |
+
)
|
| 151 |
+
)
|
| 152 |
+
(classifier): RobertaClassificationHead(
|
| 153 |
+
(dense): Linear(in_features=768, out_features=768, bias=True)
|
| 154 |
+
(dropout): Dropout(p=0.1, inplace=False)
|
| 155 |
+
(out_proj): Linear(in_features=768, out_features=2, bias=True)
|
| 156 |
+
)
|
| 157 |
+
)
|
| 158 |
+
2026-04-15 11:40:25,734 - INFO - train_pipeline - ===== Tokenizer Summary =====
|
| 159 |
+
2026-04-15 11:40:25,811 - INFO - train_pipeline - Vocab size: 50265 | Special tokens: ['<s>', '</s>', '<unk>', '<pad>', '<mask>']
|
| 160 |
+
2026-04-15 11:40:25,830 - INFO - train_pipeline - ===== End of Architecture Log =====
|
| 161 |
+
2026-04-15 11:40:25,852 - INFO - train_pipeline - Base model weights frozen – only classifier head will be trained.
|
| 162 |
+
2026-04-15 11:40:27,878 - INFO - train_pipeline - === Starting training ===
|
| 163 |
+
2026-04-15 11:40:23,361 - INFO - train_pipeline - Logging to ./output_checkpoints/codebert-base-cross-entropy/training.log
|
| 164 |
+
2026-04-15 11:40:23,369 - INFO - train_pipeline - Loading model & tokenizer for 'microsoft/codebert-base'
|
| 165 |
+
2026-04-15 11:40:25,679 - INFO - train_pipeline - Model placed on cuda
|
| 166 |
+
2026-04-15 11:40:25,694 - INFO - train_pipeline - ===== Model Architecture =====
|
| 167 |
+
2026-04-15 11:40:25,708 - INFO - train_pipeline -
|
| 168 |
+
RobertaForSequenceClassification(
|
| 169 |
+
(roberta): RobertaModel(
|
| 170 |
+
(embeddings): RobertaEmbeddings(
|
| 171 |
+
(word_embeddings): Embedding(50265, 768, padding_idx=1)
|
| 172 |
+
(position_embeddings): Embedding(514, 768, padding_idx=1)
|
| 173 |
+
(token_type_embeddings): Embedding(1, 768)
|
| 174 |
+
(LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
|
| 175 |
+
(dropout): Dropout(p=0.1, inplace=False)
|
| 176 |
+
)
|
| 177 |
+
(encoder): RobertaEncoder(
|
| 178 |
+
(layer): ModuleList(
|
| 179 |
+
(0-11): 12 x RobertaLayer(
|
| 180 |
+
(attention): RobertaAttention(
|
| 181 |
+
(self): RobertaSdpaSelfAttention(
|
| 182 |
+
(query): Linear(in_features=768, out_features=768, bias=True)
|
| 183 |
+
(key): Linear(in_features=768, out_features=768, bias=True)
|
| 184 |
+
(value): Linear(in_features=768, out_features=768, bias=True)
|
| 185 |
+
(dropout): Dropout(p=0.1, inplace=False)
|
| 186 |
+
)
|
| 187 |
+
(output): RobertaSelfOutput(
|
| 188 |
+
(dense): Linear(in_features=768, out_features=768, bias=True)
|
| 189 |
+
(LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
|
| 190 |
+
(dropout): Dropout(p=0.1, inplace=False)
|
| 191 |
+
)
|
| 192 |
+
)
|
| 193 |
+
(intermediate): RobertaIntermediate(
|
| 194 |
+
(dense): Linear(in_features=768, out_features=3072, bias=True)
|
| 195 |
+
(intermediate_act_fn): GELUActivation()
|
| 196 |
+
)
|
| 197 |
+
(output): RobertaOutput(
|
| 198 |
+
(dense): Linear(in_features=3072, out_features=768, bias=True)
|
| 199 |
+
(LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
|
| 200 |
+
(dropout): Dropout(p=0.1, inplace=False)
|
| 201 |
+
)
|
| 202 |
+
)
|
| 203 |
+
)
|
| 204 |
+
)
|
| 205 |
+
)
|
| 206 |
+
(classifier): RobertaClassificationHead(
|
| 207 |
+
(dense): Linear(in_features=768, out_features=768, bias=True)
|
| 208 |
+
(dropout): Dropout(p=0.1, inplace=False)
|
| 209 |
+
(out_proj): Linear(in_features=768, out_features=2, bias=True)
|
| 210 |
+
)
|
| 211 |
+
)
|
| 212 |
+
2026-04-15 11:40:25,734 - INFO - train_pipeline - ===== Tokenizer Summary =====
|
| 213 |
+
2026-04-15 11:40:25,811 - INFO - train_pipeline - Vocab size: 50265 | Special tokens: ['<s>', '</s>', '<unk>', '<pad>', '<mask>']
|
| 214 |
+
2026-04-15 11:40:25,830 - INFO - train_pipeline - ===== End of Architecture Log =====
|
| 215 |
+
2026-04-15 11:40:25,852 - INFO - train_pipeline - Base model weights frozen – only classifier head will be trained.
|
| 216 |
+
2026-04-15 11:40:27,878 - INFO - train_pipeline - === Starting training ===
|
| 217 |
+
2026-04-15 11:40:23,361 - INFO - train_pipeline - Logging to ./output_checkpoints/codebert-base-cross-entropy/training.log
|
| 218 |
+
2026-04-15 11:40:23,369 - INFO - train_pipeline - Loading model & tokenizer for 'microsoft/codebert-base'
|
| 219 |
+
2026-04-15 11:40:25,679 - INFO - train_pipeline - Model placed on cuda
|
| 220 |
+
2026-04-15 11:40:25,694 - INFO - train_pipeline - ===== Model Architecture =====
|
| 221 |
+
2026-04-15 11:40:25,708 - INFO - train_pipeline -
|
| 222 |
+
RobertaForSequenceClassification(
|
| 223 |
+
(roberta): RobertaModel(
|
| 224 |
+
(embeddings): RobertaEmbeddings(
|
| 225 |
+
(word_embeddings): Embedding(50265, 768, padding_idx=1)
|
| 226 |
+
(position_embeddings): Embedding(514, 768, padding_idx=1)
|
| 227 |
+
(token_type_embeddings): Embedding(1, 768)
|
| 228 |
+
(LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
|
| 229 |
+
(dropout): Dropout(p=0.1, inplace=False)
|
| 230 |
+
)
|
| 231 |
+
(encoder): RobertaEncoder(
|
| 232 |
+
(layer): ModuleList(
|
| 233 |
+
(0-11): 12 x RobertaLayer(
|
| 234 |
+
(attention): RobertaAttention(
|
| 235 |
+
(self): RobertaSdpaSelfAttention(
|
| 236 |
+
(query): Linear(in_features=768, out_features=768, bias=True)
|
| 237 |
+
(key): Linear(in_features=768, out_features=768, bias=True)
|
| 238 |
+
(value): Linear(in_features=768, out_features=768, bias=True)
|
| 239 |
+
(dropout): Dropout(p=0.1, inplace=False)
|
| 240 |
+
)
|
| 241 |
+
(output): RobertaSelfOutput(
|
| 242 |
+
(dense): Linear(in_features=768, out_features=768, bias=True)
|
| 243 |
+
(LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
|
| 244 |
+
(dropout): Dropout(p=0.1, inplace=False)
|
| 245 |
+
)
|
| 246 |
+
)
|
| 247 |
+
(intermediate): RobertaIntermediate(
|
| 248 |
+
(dense): Linear(in_features=768, out_features=3072, bias=True)
|
| 249 |
+
(intermediate_act_fn): GELUActivation()
|
| 250 |
+
)
|
| 251 |
+
(output): RobertaOutput(
|
| 252 |
+
(dense): Linear(in_features=3072, out_features=768, bias=True)
|
| 253 |
+
(LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
|
| 254 |
+
(dropout): Dropout(p=0.1, inplace=False)
|
| 255 |
+
)
|
| 256 |
+
)
|
| 257 |
+
)
|
| 258 |
+
)
|
| 259 |
+
)
|
| 260 |
+
(classifier): RobertaClassificationHead(
|
| 261 |
+
(dense): Linear(in_features=768, out_features=768, bias=True)
|
| 262 |
+
(dropout): Dropout(p=0.1, inplace=False)
|
| 263 |
+
(out_proj): Linear(in_features=768, out_features=2, bias=True)
|
| 264 |
+
)
|
| 265 |
+
)
|
| 266 |
+
2026-04-15 11:40:25,734 - INFO - train_pipeline - ===== Tokenizer Summary =====
|
| 267 |
+
2026-04-15 11:40:25,811 - INFO - train_pipeline - Vocab size: 50265 | Special tokens: ['<s>', '</s>', '<unk>', '<pad>', '<mask>']
|
| 268 |
+
2026-04-15 11:40:25,830 - INFO - train_pipeline - ===== End of Architecture Log =====
|
| 269 |
+
2026-04-15 11:40:25,852 - INFO - train_pipeline - Base model weights frozen – only classifier head will be trained.
|
| 270 |
+
2026-04-15 11:40:27,878 - INFO - train_pipeline - === Starting training ===
|
| 271 |
+
2026-04-15 11:40:23,361 - INFO - train_pipeline - Logging to ./output_checkpoints/codebert-base-cross-entropy/training.log
|
| 272 |
+
2026-04-15 11:40:23,369 - INFO - train_pipeline - Loading model & tokenizer for 'microsoft/codebert-base'
|
| 273 |
+
2026-04-15 11:40:25,679 - INFO - train_pipeline - Model placed on cuda
|
| 274 |
+
2026-04-15 11:40:25,694 - INFO - train_pipeline - ===== Model Architecture =====
|
| 275 |
+
2026-04-15 11:40:25,708 - INFO - train_pipeline -
|
| 276 |
+
RobertaForSequenceClassification(
|
| 277 |
+
(roberta): RobertaModel(
|
| 278 |
+
(embeddings): RobertaEmbeddings(
|
| 279 |
+
(word_embeddings): Embedding(50265, 768, padding_idx=1)
|
| 280 |
+
(position_embeddings): Embedding(514, 768, padding_idx=1)
|
| 281 |
+
(token_type_embeddings): Embedding(1, 768)
|
| 282 |
+
(LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
|
| 283 |
+
(dropout): Dropout(p=0.1, inplace=False)
|
| 284 |
+
)
|
| 285 |
+
(encoder): RobertaEncoder(
|
| 286 |
+
(layer): ModuleList(
|
| 287 |
+
(0-11): 12 x RobertaLayer(
|
| 288 |
+
(attention): RobertaAttention(
|
| 289 |
+
(self): RobertaSdpaSelfAttention(
|
| 290 |
+
(query): Linear(in_features=768, out_features=768, bias=True)
|
| 291 |
+
(key): Linear(in_features=768, out_features=768, bias=True)
|
| 292 |
+
(value): Linear(in_features=768, out_features=768, bias=True)
|
| 293 |
+
(dropout): Dropout(p=0.1, inplace=False)
|
| 294 |
+
)
|
| 295 |
+
(output): RobertaSelfOutput(
|
| 296 |
+
(dense): Linear(in_features=768, out_features=768, bias=True)
|
| 297 |
+
(LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
|
| 298 |
+
(dropout): Dropout(p=0.1, inplace=False)
|
| 299 |
+
)
|
| 300 |
+
)
|
| 301 |
+
(intermediate): RobertaIntermediate(
|
| 302 |
+
(dense): Linear(in_features=768, out_features=3072, bias=True)
|
| 303 |
+
(intermediate_act_fn): GELUActivation()
|
| 304 |
+
)
|
| 305 |
+
(output): RobertaOutput(
|
| 306 |
+
(dense): Linear(in_features=3072, out_features=768, bias=True)
|
| 307 |
+
(LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
|
| 308 |
+
(dropout): Dropout(p=0.1, inplace=False)
|
| 309 |
+
)
|
| 310 |
+
)
|
| 311 |
+
)
|
| 312 |
+
)
|
| 313 |
+
)
|
| 314 |
+
(classifier): RobertaClassificationHead(
|
| 315 |
+
(dense): Linear(in_features=768, out_features=768, bias=True)
|
| 316 |
+
(dropout): Dropout(p=0.1, inplace=False)
|
| 317 |
+
(out_proj): Linear(in_features=768, out_features=2, bias=True)
|
| 318 |
+
)
|
| 319 |
+
)
|
| 320 |
+
2026-04-15 11:40:25,734 - INFO - train_pipeline - ===== Tokenizer Summary =====
|
| 321 |
+
2026-04-15 11:40:25,811 - INFO - train_pipeline - Vocab size: 50265 | Special tokens: ['<s>', '</s>', '<unk>', '<pad>', '<mask>']
|
| 322 |
+
2026-04-15 11:40:25,830 - INFO - train_pipeline - ===== End of Architecture Log =====
|
| 323 |
+
2026-04-15 11:40:25,852 - INFO - train_pipeline - Base model weights frozen – only classifier head will be trained.
|
| 324 |
+
2026-04-15 11:40:27,878 - INFO - train_pipeline - === Starting training ===
|