End of training

.gitattributes

@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text
+unigram.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,62 @@
+---
+license: apache-2.0
+base_model: shibing624/text2vec-base-multilingual
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: w2v128b128l
+  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. -->
+
+# w2v128b128l
+
+This model is a fine-tuned version of [shibing624/text2vec-base-multilingual](https://huggingface.co/shibing624/text2vec-base-multilingual) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8963
+- Accuracy: 0.6528
+
+## 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: 1e-05
+- train_batch_size: 128
+- eval_batch_size: 128
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.1613        | 1.0   | 1407 | 1.0185          | 0.6048   |
+| 0.9495        | 2.0   | 2814 | 0.9233          | 0.6422   |
+| 0.8848        | 3.0   | 4221 | 0.8963          | 0.6528   |
+
+
+### Framework versions
+
+- Transformers 4.41.0
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

config.json

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+  "_name_or_path": "shibing624/text2vec-base-multilingual",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 384,
+  "id2label": {
+    "0": "Gogol",
+    "1": "Dostoevsky",
+    "2": "Chekhov",
+    "3": "Gorky",
+    "4": "Tolstoy"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 1536,
+  "label2id": {
+    "Chekhov": 2,
+    "Dostoevsky": 1,
+    "Gogol": 0,
+    "Gorky": 3,
+    "Tolstoy": 4
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.41.0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 250037
+}

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runs/May25_12-46-09_56ae490701f9/events.out.tfevents.1716641171.56ae490701f9.433.3

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special_tokens_map.json

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tokenizer_config.json

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