End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: albert/albert-xlarge-v1
+tags:
+- generated_from_trainer
+model-index:
+- name: d4bb5efa4446fd09c3cec4ee6b7f9f2f
+  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. -->
+
+# d4bb5efa4446fd09c3cec4ee6b7f9f2f
+
+This model is a fine-tuned version of [albert/albert-xlarge-v1](https://huggingface.co/albert/albert-xlarge-v1) on the nyu-mll/glue dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4714
+- Data Size: 1.0
+- Epoch Runtime: 11.8008
+- Mse: 0.4716
+- Mae: 0.5129
+- R2: 0.7891
+
+## 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 | Mse    | Mae    | R2      |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------------:|:------:|:------:|:-------:|
+| No log        | 0     | 0    | 5.0435          | 0         | 1.3857        | 5.0446 | 1.8525 | -1.2566 |
+| No log        | 1     | 179  | 2.4450          | 0.0078    | 1.7986        | 2.4458 | 1.3442 | -0.0941 |
+| No log        | 2     | 358  | 2.9948          | 0.0156    | 1.7744        | 2.9954 | 1.4071 | -0.3400 |
+| No log        | 3     | 537  | 2.0540          | 0.0312    | 1.9364        | 2.0545 | 1.1773 | 0.0809  |
+| No log        | 4     | 716  | 1.9062          | 0.0625    | 2.3199        | 1.9064 | 1.1118 | 0.1472  |
+| No log        | 5     | 895  | 1.9882          | 0.125     | 2.8993        | 1.9884 | 1.1664 | 0.1105  |
+| 0.0911        | 6     | 1074 | 1.2368          | 0.25      | 4.2179        | 1.2374 | 0.8941 | 0.4465  |
+| 1.0993        | 7     | 1253 | 1.0669          | 0.5       | 6.6649        | 1.0674 | 0.8623 | 0.5225  |
+| 0.6755        | 8.0   | 1432 | 0.9378          | 1.0       | 12.1193       | 0.9379 | 0.7424 | 0.5804  |
+| 0.6614        | 9.0   | 1611 | 0.5567          | 1.0       | 11.7972       | 0.5569 | 0.5640 | 0.7509  |
+| 0.4698        | 10.0  | 1790 | 0.4544          | 1.0       | 11.7081       | 0.4547 | 0.5174 | 0.7966  |
+| 0.485         | 11.0  | 1969 | 0.5114          | 1.0       | 11.7362       | 0.5117 | 0.5589 | 0.7711  |
+| 0.3829        | 12.0  | 2148 | 0.4850          | 1.0       | 11.7300       | 0.4853 | 0.5314 | 0.7829  |
+| 0.3277        | 13.0  | 2327 | 0.5984          | 1.0       | 11.8775       | 0.5986 | 0.5964 | 0.7322  |
+| 0.2764        | 14.0  | 2506 | 0.4714          | 1.0       | 11.8008       | 0.4716 | 0.5129 | 0.7891  |
+
+
+### 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": 0.1,
+  "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",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 2048,
+  "id2label": {
+    "0": "LABEL_0"
+  },
+  "initializer_range": 0.02,
+  "inner_group_num": 1,
+  "intermediate_size": 8192,
+  "label2id": {
+    "LABEL_0": 0
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "albert",
+  "net_structure_type": 0,
+  "num_attention_heads": 16,
+  "num_hidden_groups": 1,
+  "num_hidden_layers": 24,
+  "num_memory_blocks": 0,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "regression",
+  "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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+{
+  "bos_token": "[CLS]",
+  "cls_token": "[CLS]",
+  "eos_token": "[SEP]",
+  "mask_token": {
+    "content": "[MASK]",
+    "lstrip": true,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": "<pad>",
+  "sep_token": "[SEP]",
+  "unk_token": "<unk>"
+}

spiece.model

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tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<pad>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "normalized": false,
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+      "special": true
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+      "lstrip": true,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+  },
+  "bos_token": "[CLS]",
+  "clean_up_tokenization_spaces": false,
+  "cls_token": "[CLS]",
+  "do_lower_case": true,
+  "eos_token": "[SEP]",
+  "extra_special_tokens": {},
+  "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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