FrinzTheCoder/bert-base-multilingual-cased-ron

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-ron
   results: []
@@ -17,11 +18,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # bert-base-multilingual-cased-ron
 
-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: 0.2138
-- Accuracy: 0.6918
-- F1: 0.5657
+- Loss: 0.0552
+- Accuracy: 0.8696
+- F1 Binary: 0.8054
+- Precision: 0.7226
+- Recall: 0.9096
 
 ## 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: 37
 - num_epochs: 4
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| No log        | 1.0   | 156  | 0.2185          | 0.6918   | 0.5657 |
-| No log        | 2.0   | 312  | 0.2133          | 0.6918   | 0.5657 |
-| No log        | 3.0   | 468  | 0.2304          | 0.6918   | 0.5657 |
-| 0.2213        | 4.0   | 624  | 0.2138          | 0.6918   | 0.5657 |
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Binary | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:---------:|:------:|
+| No log        | 1.0   | 187  | 0.0957          | 0.7502   | 0.6166    | 0.5662    | 0.6768 |
+| No log        | 2.0   | 374  | 0.0623          | 0.7787   | 0.7014    | 0.5849    | 0.8757 |
+| 0.0661        | 3.0   | 561  | 0.0603          | 0.8414   | 0.7736    | 0.6711    | 0.9130 |
+| 0.0661        | 4.0   | 748  | 0.0552          | 0.8696   | 0.8054    | 0.7226    | 0.9096 |
 
 
 ### 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:d105bdaf0d1031aade79f3e91e86c2e791cea41ba2964637a8939573e8deb8ed
-size 711440380
+oid sha256:79646eeb71d6a079e6b2219e9c37b392cde24bacbd29f4c7ecb33478a5df5b96
+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:cffc661e237a55fcafe910801d1639ae652384863edd3cb1c1aaca17f11987e4
-size 5240
+oid sha256:4fab365643f580ceed38444d1fa61f962035eb1523efaaa49ee6d2ade3e4adb0
+size 5368