Update IR model to reshapeable version.
Browse files- README.md +4 -2
- all_results.json +6 -6
- config.json +1 -1
- eval_results.json +3 -3
- model.onnx +0 -3
- nncf_output.log +2 -1
- openvino_config.json +3 -3
- openvino_model.bin +2 -2
- openvino_model.xml +0 -0
- pytorch_model.bin +1 -1
- tokenizer.json +2 -16
- train_results.json +3 -3
- trainer_state.json +27 -27
- training_args.bin +2 -2
README.md
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@@ -17,6 +17,8 @@ model-index:
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dataset:
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name: GLUE SST2
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type: glue
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args: sst2
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metrics:
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- name: Accuracy
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@@ -30,7 +32,7 @@ should probably proofread and complete it, then remove this comment. -->
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# jpqd-bert-base-ft-sst2
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> **Note**
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> This model was trained for only 1 epoch and is shared for testing purposes
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the GLUE SST2 dataset.
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It achieves the following results on the evaluation set:
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### Framework versions
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- Transformers 4.
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- Pytorch 1.13.1+cu117
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- Datasets 2.8.0
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- Tokenizers 0.13.2
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dataset:
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name: GLUE SST2
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type: glue
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config: sst2
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split: validation
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args: sst2
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metrics:
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- name: Accuracy
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# jpqd-bert-base-ft-sst2
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> **Note**
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+
> This model was trained for only 1 epoch and is shared for testing purposes.
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the GLUE SST2 dataset.
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It achieves the following results on the evaluation set:
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### Framework versions
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- Transformers 4.26.1
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- Pytorch 1.13.1+cu117
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- Datasets 2.8.0
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- Tokenizers 0.13.2
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all_results.json
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"epoch": 1.0,
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"eval_accuracy": 0.9254587155963303,
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"eval_loss": 0.21810248494148254,
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"eval_runtime": 22.
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"eval_samples": 872,
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"eval_samples_per_second": 39.
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"eval_steps_per_second": 4.
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"train_loss": 0.40093172477146793,
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"train_samples_per_second":
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"train_steps_per_second": 1.
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}
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"epoch": 1.0,
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"eval_steps_per_second": 4.885,
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}
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config.json
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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"torch_dtype": "float32",
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"transformers_version": "4.
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"type_vocab_size": 2,
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"use_cache": true,
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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"torch_dtype": "float32",
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"transformers_version": "4.26.1",
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"type_vocab_size": 2,
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eval_results.json
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"epoch": 1.0,
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"epoch": 1.0,
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model.onnx
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nncf_output.log
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@@ -75,6 +75,8 @@ INFO:nncf:Not adding activation input quantizer for operation: 352 BertForSequen
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INFO:nncf:Not adding activation input quantizer for operation: 357 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertOutput[output]/__add___0
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INFO:nncf:Not adding activation input quantizer for operation: 358 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0
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INFO:nncf:Collecting tensor statistics |████████████████| 1 / 1
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INFO:nncf:BatchNorm statistics adaptation |██ | 1 / 7
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INFO:nncf:BatchNorm statistics adaptation |████ | 2 / 7
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INFO:nncf:BatchNorm statistics adaptation |██████ | 3 / 7
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Epoch 0 || 8 | 100.00 % (77 / 77) | 100.00 % (101 / | 100.00 % (178 / |
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Epoch 0 || | | 101) | 178) |
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Epoch 0 |+--------------+---------------------+--------------------+--------------------+
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INFO:nncf:Movement sparsity scheduler updates importance threshold and regularizationfactor per optimizer step, but steps_per_epoch was not set in config. Will measure the actual steps per epoch as signaled by a .epoch_step() call.
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INFO:nncf:Not adding activation input quantizer for operation: 357 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertOutput[output]/__add___0
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INFO:nncf:Not adding activation input quantizer for operation: 358 BertForSequenceClassification/BertModel[bert]/BertEncoder[encoder]/ModuleList[layer]/BertLayer[11]/BertOutput[output]/NNCFLayerNorm[LayerNorm]/layer_norm_0
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INFO:nncf:Collecting tensor statistics |████████████████| 1 / 1
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INFO:nncf:Compiling and loading torch extension: quantized_functions_cuda...
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INFO:nncf:Finished loading torch extension: quantized_functions_cuda
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INFO:nncf:BatchNorm statistics adaptation |██ | 1 / 7
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INFO:nncf:BatchNorm statistics adaptation |████ | 2 / 7
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INFO:nncf:BatchNorm statistics adaptation |██████ | 3 / 7
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Epoch 0 || 8 | 100.00 % (77 / 77) | 100.00 % (101 / | 100.00 % (178 / |
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Epoch 0 || | | 101) | 178) |
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Epoch 0 |+--------------+---------------------+--------------------+--------------------+
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openvino_config.json
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openvino_model.bin
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pytorch_model.bin
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"max_steps": 2105,
|
training_args.bin
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
-
size
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:512755fad1ec8d16b5f8c62bc77ce4f3655b8f55c801d2452ac80202929c67a1
|
3 |
+
size 3579
|