Training complete

README.md

@@ -1,5 +1,6 @@
 ---
 license: apache-2.0
+base_model: bert-base-uncased
 tags:
 - classification
 - generated_from_trainer
@@ -17,12 +18,12 @@ model-index:
       name: poem_sentiment
       type: poem_sentiment
       config: default
-      split: train
+      split: test
       args: default
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9038461538461539
+      value: 0.8461538461538461
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +33,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the poem_sentiment dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.5088
-- Accuracy: 0.9038
+- Loss: 0.5423
+- Accuracy: 0.8462
 
 ## Model description
 
@@ -64,14 +65,14 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 1.0   | 112  | 0.4324          | 0.8654   |
-| No log        | 2.0   | 224  | 0.4070          | 0.875    |
-| No log        | 3.0   | 336  | 0.5088          | 0.9038   |
+| No log        | 1.0   | 112  | 0.4428          | 0.8558   |
+| No log        | 2.0   | 224  | 0.4875          | 0.8462   |
+| No log        | 3.0   | 336  | 0.5423          | 0.8462   |
 
 
 ### Framework versions
 
-- Transformers 4.25.1
-- Pytorch 1.13.0+cu116
-- Datasets 2.8.0
-- Tokenizers 0.13.2
+- Transformers 4.36.0
+- Pytorch 2.1.0+cu118
+- Datasets 2.15.0
+- Tokenizers 0.15.0

config.json

@@ -32,7 +32,7 @@
   "position_embedding_type": "absolute",
   "problem_type": "single_label_classification",
   "torch_dtype": "float32",
-  "transformers_version": "4.25.1",
+  "transformers_version": "4.36.0",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 30522

model.safetensors

@@ -0,0 +1,3 @@
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+size 437964800

tokenizer_config.json

@@ -1,12 +1,53 @@
 {
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "101": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "102": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "103": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": true,
   "cls_token": "[CLS]",
   "do_lower_case": true,
   "mask_token": "[MASK]",
   "model_max_length": 512,
-  "name_or_path": "bert-base-uncased",
   "pad_token": "[PAD]",
   "sep_token": "[SEP]",
-  "special_tokens_map_file": null,
   "strip_accents": null,
   "tokenize_chinese_chars": true,
   "tokenizer_class": "BertTokenizer",

training_args.bin

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-size 3451
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+size 4728