Training in progress, step 500

README.md

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+---
+license: apache-2.0
+base_model: google/mt5-large
+tags:
+- generated_from_trainer
+model-index:
+- name: results
+  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. -->
+
+# results
+
+This model is a fine-tuned version of [google/mt5-large](https://huggingface.co/google/mt5-large) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.9627
+- Loc: {'precision': 0.07002967359050445, 'recall': 0.13817330210772832, 'f1': 0.09294998030720757, 'number': 854}
+- Org: {'precision': 0.06141439205955335, 'recall': 0.1523076923076923, 'f1': 0.08753315649867373, 'number': 650}
+- Per: {'precision': 0.030874785591766724, 'recall': 0.07741935483870968, 'f1': 0.04414469650521153, 'number': 465}
+- Overall Precision: 0.0567
+- Overall Recall: 0.1285
+- Overall F1: 0.0787
+- Overall Accuracy: 0.3287
+
+## 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
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 4
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Loc                                                                                                         | Org                                                                                                         | Per                                                                                                          | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:-----------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
+| 3.8187        | 2.0   | 10   | 3.1219          | {'precision': 0.06360022714366836, 'recall': 0.13114754098360656, 'f1': 0.08565965583173997, 'number': 854} | {'precision': 0.05763688760806916, 'recall': 0.15384615384615385, 'f1': 0.08385744234800839, 'number': 650} | {'precision': 0.027879677182685254, 'recall': 0.08172043010752689, 'f1': 0.04157549234135668, 'number': 465} | 0.0515            | 0.1270         | 0.0732     | 0.2983           |
+| 3.2942        | 4.0   | 20   | 2.9627          | {'precision': 0.07002967359050445, 'recall': 0.13817330210772832, 'f1': 0.09294998030720757, 'number': 854} | {'precision': 0.06141439205955335, 'recall': 0.1523076923076923, 'f1': 0.08753315649867373, 'number': 650}  | {'precision': 0.030874785591766724, 'recall': 0.07741935483870968, 'f1': 0.04414469650521153, 'number': 465} | 0.0567            | 0.1285         | 0.0787     | 0.3287           |
+
+
+### Framework versions
+
+- Transformers 4.39.3
+- Pytorch 1.11.0a0+17540c5
+- Datasets 2.20.0
+- Tokenizers 0.15.2

config.json

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+{
+  "_name_or_path": "google/mt5-large",
+  "architectures": [
+    "MT5ForTokenClassification"
+  ],
+  "classifier_dropout": 0.0,
+  "d_ff": 2816,
+  "d_kv": 64,
+  "d_model": 1024,
+  "decoder_start_token_id": 0,
+  "dense_act_fn": "gelu_new",
+  "dropout_rate": 0.1,
+  "eos_token_id": 1,
+  "feed_forward_proj": "gated-gelu",
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2",
+    "3": "LABEL_3",
+    "4": "LABEL_4",
+    "5": "LABEL_5",
+    "6": "LABEL_6"
+  },
+  "initializer_factor": 1.0,
+  "is_encoder_decoder": true,
+  "is_gated_act": true,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2,
+    "LABEL_3": 3,
+    "LABEL_4": 4,
+    "LABEL_5": 5,
+    "LABEL_6": 6
+  },
+  "layer_norm_epsilon": 1e-06,
+  "model_type": "mt5",
+  "num_decoder_layers": 24,
+  "num_heads": 16,
+  "num_layers": 24,
+  "output_past": true,
+  "pad_token_id": 0,
+  "relative_attention_max_distance": 128,
+  "relative_attention_num_buckets": 32,
+  "tie_word_embeddings": false,
+  "tokenizer_class": "T5Tokenizer",
+  "torch_dtype": "float32",
+  "transformers_version": "4.39.3",
+  "use_cache": true,
+  "vocab_size": 250112
+}

model.safetensors

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training_args.bin

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