FrinzTheCoder/bert-base-multilingual-cased-chn

README.md

@@ -1,12 +1,13 @@
 ---
 library_name: transformers
 license: apache-2.0
-base_model: bert-base-multilingual-cased
+base_model: google-bert/bert-base-multilingual-cased
 tags:
 - generated_from_trainer
 metrics:
 - accuracy
-- f1
+- precision
+- recall
 model-index:
 - name: bert-base-multilingual-cased-chn
   results: []
@@ -17,11 +18,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # bert-base-multilingual-cased-chn
 
-This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset.
+This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1447
-- Accuracy: 0.8250
-- F1: 0.7458
+- Loss: 0.1006
+- Accuracy: 0.8491
+- F1 Binary: 0.6401
+- Precision: 0.5413
+- Recall: 0.7831
 
 ## Model description
 
@@ -40,27 +43,28 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 0.0003
+- learning_rate: 3e-05
 - train_batch_size: 64
 - eval_batch_size: 16
 - seed: 42
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 39
 - num_epochs: 4
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| No log        | 1.0   | 166  | 0.1564          | 0.8250   | 0.7458 |
-| No log        | 2.0   | 332  | 0.1494          | 0.8250   | 0.7458 |
-| No log        | 3.0   | 498  | 0.1468          | 0.8250   | 0.7458 |
-| 0.1521        | 4.0   | 664  | 0.1447          | 0.8250   | 0.7458 |
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Binary | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:---------:|:------:|
+| No log        | 1.0   | 199  | 0.0737          | 0.8059   | 0.5746    | 0.4602    | 0.7647 |
+| No log        | 2.0   | 398  | 0.0789          | 0.8437   | 0.6190    | 0.5317    | 0.7408 |
+| 0.0623        | 3.0   | 597  | 0.1075          | 0.8756   | 0.6451    | 0.6309    | 0.6599 |
+| 0.0623        | 4.0   | 796  | 0.1006          | 0.8491   | 0.6401    | 0.5413    | 0.7831 |
 
 
 ### Framework versions
 
-- Transformers 4.44.2
-- Pytorch 2.4.1+cu121
+- Transformers 4.47.0
+- Pytorch 2.5.1+cu121
 - Datasets 3.2.0
-- Tokenizers 0.19.1
+- Tokenizers 0.21.0

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "bert-base-multilingual-cased",
+  "_name_or_path": "google-bert/bert-base-multilingual-cased",
   "architectures": [
     "BertForSequenceClassification"
   ],
@@ -9,14 +9,8 @@
   "hidden_act": "gelu",
   "hidden_dropout_prob": 0.1,
   "hidden_size": 768,
-  "id2label": {
-    "0": "LABEL_0"
-  },
   "initializer_range": 0.02,
   "intermediate_size": 3072,
-  "label2id": {
-    "LABEL_0": 0
-  },
   "layer_norm_eps": 1e-12,
   "max_position_embeddings": 512,
   "model_type": "bert",
@@ -29,9 +23,8 @@
   "pooler_size_per_head": 128,
   "pooler_type": "first_token_transform",
   "position_embedding_type": "absolute",
-  "problem_type": "regression",
   "torch_dtype": "float32",
-  "transformers_version": "4.44.2",
+  "transformers_version": "4.47.0",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 119547

model.safetensors

@@ -1,3 +1,3 @@
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-oid sha256:31327a2bb02c462dc75cb6b38151db0fe30c5ce5db601412152520966c33f235
-size 711440380
+oid sha256:f579269ea829fa3e5fe6f683bac005170c3620071c307fcd80173e89a79fd185
+size 711443456

tokenizer.json

@@ -7,9 +7,7 @@
     "stride": 0
   },
   "padding": {
-    "strategy": {
-      "Fixed": 512
-    },
+    "strategy": "BatchLongest",
     "direction": "Right",
     "pad_to_multiple_of": null,
     "pad_id": 0,

tokenizer_config.json

@@ -41,9 +41,10 @@
       "special": true
     }
   },
-  "clean_up_tokenization_spaces": true,
+  "clean_up_tokenization_spaces": false,
   "cls_token": "[CLS]",
   "do_lower_case": false,
+  "extra_special_tokens": {},
   "mask_token": "[MASK]",
   "model_max_length": 512,
   "pad_token": "[PAD]",

training_args.bin

@@ -1,3 +1,3 @@
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-oid sha256:881128ecad115f9461151b87b5e14c855d4fea84d12c0ae2a0ef3996bf081f3d
-size 5240
+oid sha256:0a7e58b7e87da60421ce0a55d97a3d357eb01163315900d5bbc3d816a5306bd2
+size 5368