End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: albert/albert-base-v2
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: b2a13bdfdbee03869078392ce31ca69a
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# b2a13bdfdbee03869078392ce31ca69a
+
+This model is a fine-tuned version of [albert/albert-base-v2](https://huggingface.co/albert/albert-base-v2) on the contemmcm/cls_20newsgroups dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7541
+- Data Size: 1.0
+- Epoch Runtime: 29.5942
+- Accuracy: 0.8377
+- F1 Macro: 0.8391
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 4
+- total_train_batch_size: 32
+- total_eval_batch_size: 32
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: constant
+- num_epochs: 50
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Data Size | Epoch Runtime | Accuracy | F1 Macro |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:-------------:|:--------:|:--------:|
+| No log        | 0     | 0     | 3.0820          | 0         | 2.9678        | 0.0605   | 0.0151   |
+| No log        | 1     | 499   | 3.0567          | 0.0078    | 3.4622        | 0.0504   | 0.0048   |
+| 0.031         | 2     | 998   | 3.0091          | 0.0156    | 3.3477        | 0.0391   | 0.0112   |
+| 0.0543        | 3     | 1497  | 3.0022          | 0.0312    | 3.7892        | 0.0554   | 0.0097   |
+| 0.1023        | 4     | 1996  | 3.0063          | 0.0625    | 4.8024        | 0.0423   | 0.0041   |
+| 3.0041        | 5     | 2495  | 2.9995          | 0.125     | 6.3555        | 0.0517   | 0.0049   |
+| 2.991         | 6     | 2994  | 3.0435          | 0.25      | 9.6819        | 0.0665   | 0.0181   |
+| 1.949         | 7     | 3493  | 1.7583          | 0.5       | 16.3085       | 0.3546   | 0.2790   |
+| 1.2499        | 8.0   | 3992  | 1.1927          | 1.0       | 29.7099       | 0.5761   | 0.5240   |
+| 1.0707        | 9.0   | 4491  | 1.0339          | 1.0       | 29.6584       | 0.6615   | 0.6368   |
+| 0.8532        | 10.0  | 4990  | 0.9110          | 1.0       | 29.5331       | 0.7132   | 0.6890   |
+| 0.634         | 11.0  | 5489  | 0.8023          | 1.0       | 29.7321       | 0.7641   | 0.7594   |
+| 0.5863        | 12.0  | 5988  | 0.7403          | 1.0       | 29.5549       | 0.8062   | 0.8034   |
+| 0.5222        | 13.0  | 6487  | 0.6932          | 1.0       | 29.6895       | 0.8133   | 0.8116   |
+| 0.4108        | 14.0  | 6986  | 0.7164          | 1.0       | 29.6142       | 0.8193   | 0.8177   |
+| 0.4135        | 15.0  | 7485  | 0.7475          | 1.0       | 29.4822       | 0.8233   | 0.8194   |
+| 0.3594        | 16.0  | 7984  | 0.7092          | 1.0       | 29.5987       | 0.8274   | 0.8259   |
+| 0.3296        | 17.0  | 8483  | 0.6517          | 1.0       | 29.6032       | 0.8475   | 0.8450   |
+| 0.2996        | 18.0  | 8982  | 0.6841          | 1.0       | 29.5800       | 0.8402   | 0.8352   |
+| 0.2559        | 19.0  | 9481  | 0.6700          | 1.0       | 29.5649       | 0.8511   | 0.8499   |
+| 0.25          | 20.0  | 9980  | 0.7420          | 1.0       | 29.6743       | 0.8395   | 0.8366   |
+| 0.2695        | 21.0  | 10479 | 0.7541          | 1.0       | 29.5942       | 0.8377   | 0.8391   |
+
+
+### Framework versions
+
+- Transformers 4.57.0
+- Pytorch 2.8.0+cu128
+- Datasets 4.0.0
+- Tokenizers 0.22.1

config.json

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+{
+  "architectures": [
+    "AlbertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0,
+  "bos_token_id": 2,
+  "classifier_dropout_prob": 0.1,
+  "down_scale_factor": 1,
+  "dtype": "float32",
+  "embedding_size": 128,
+  "eos_token_id": 3,
+  "gap_size": 0,
+  "hidden_act": "gelu_new",
+  "hidden_dropout_prob": 0,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2",
+    "3": "LABEL_3",
+    "4": "LABEL_4",
+    "5": "LABEL_5",
+    "6": "LABEL_6",
+    "7": "LABEL_7",
+    "8": "LABEL_8",
+    "9": "LABEL_9",
+    "10": "LABEL_10",
+    "11": "LABEL_11",
+    "12": "LABEL_12",
+    "13": "LABEL_13",
+    "14": "LABEL_14",
+    "15": "LABEL_15",
+    "16": "LABEL_16",
+    "17": "LABEL_17",
+    "18": "LABEL_18",
+    "19": "LABEL_19"
+  },
+  "initializer_range": 0.02,
+  "inner_group_num": 1,
+  "intermediate_size": 3072,
+  "label2id": {
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+    "LABEL_9": 9
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+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "albert",
+  "net_structure_type": 0,
+  "num_attention_heads": 12,
+  "num_hidden_groups": 1,
+  "num_hidden_layers": 12,
+  "num_memory_blocks": 0,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "transformers_version": "4.57.0",
+  "type_vocab_size": 2,
+  "vocab_size": 30000
+}

model.safetensors

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special_tokens_map.json

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+}

spiece.model

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tokenizer_config.json

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+  "do_lower_case": true,
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+  "keep_accents": false,
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "pad_token": "<pad>",
+  "remove_space": true,
+  "sep_token": "[SEP]",
+  "tokenizer_class": "AlbertTokenizer",
+  "unk_token": "<unk>"
+}

training_args.bin

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