CocoRoF/ModernBERT-SimCSE-multitask_v05
Browse files- 2_Dense/model.safetensors +1 -1
- README.md +751 -88
- model.safetensors +1 -1
2_Dense/model.safetensors
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version https://git-lfs.github.com/spec/v1
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size 2362528
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version https://git-lfs.github.com/spec/v1
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size 2362528
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README.md
CHANGED
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@@ -4,7 +4,7 @@ tags:
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- sentence-similarity
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- feature-extraction
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- generated_from_trainer
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-
- dataset_size:
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- loss:CosineSimilarityLoss
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base_model: CocoRoF/ModernBERT-SimCSE_v04
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widget:
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- 우리와 같은 태양계가 은하계 밖에서 존재할 수도 있을 것입니다.
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- 그 여자는 데이트하러 가는 중이다.
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- 녹색 버스가 도로를 따라 내려간다.
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pipeline_tag: sentence-similarity
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library_name: sentence-transformers
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metrics:
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type: sts_dev
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metrics:
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- type: pearson_cosine
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value: 0.
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name: Pearson Cosine
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- type: spearman_cosine
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-
value: 0.
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name: Spearman Cosine
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- type: pearson_euclidean
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value: 0.
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name: Pearson Euclidean
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- type: spearman_euclidean
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value: 0.
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name: Spearman Euclidean
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- type: pearson_manhattan
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value: 0.
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name: Pearson Manhattan
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- type: spearman_manhattan
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-
value: 0.
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name: Spearman Manhattan
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- type: pearson_dot
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value: 0.
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name: Pearson Dot
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- type: spearman_dot
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value: 0.
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name: Spearman Dot
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- type: pearson_max
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value: 0.
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name: Pearson Max
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- type: spearman_max
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value: 0.
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name: Spearman Max
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---
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# SentenceTransformer based on CocoRoF/ModernBERT-SimCSE_v04
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-
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [CocoRoF/ModernBERT-SimCSE_v04](https://huggingface.co/CocoRoF/ModernBERT-SimCSE_v04). It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
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## Model Details
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- **Maximum Sequence Length:** 512 tokens
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- **Output Dimensionality:** 768 dimensions
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- **Similarity Function:** Cosine Similarity
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-
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<!-- - **Language:** Unknown -->
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<!-- - **License:** Unknown -->
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from sentence_transformers import SentenceTransformer
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# Download from the 🤗 Hub
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-
model = SentenceTransformer("CocoRoF/ModernBERT-SimCSE-
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# Run inference
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sentences = [
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'버스가 바쁜 길을 따라 운전한다.',
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| Metric | Value |
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|:-------------------|:-----------|
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-
| pearson_cosine | 0.
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| spearman_cosine | 0.
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| pearson_euclidean | 0.
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| spearman_euclidean | 0.
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| pearson_manhattan | 0.
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| spearman_manhattan | 0.
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| pearson_dot | 0.
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| spearman_dot | 0.
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| pearson_max | 0.
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| **spearman_max** | **0.
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<!--
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## Bias, Risks and Limitations
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### Training Dataset
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####
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-
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*
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* Columns: <code>sentence1</code>, <code>sentence2</code>, and <code>score</code>
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* Approximate statistics based on the first 1000 samples:
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| | sentence1 | sentence2 | score
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-
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| type | string | string | float
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| details | <ul><li>min:
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* Samples:
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| sentence1
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-
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| <code
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| <code
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| <code
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* Loss: [<code>CosineSimilarityLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cosinesimilarityloss) with these parameters:
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```json
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{
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- `per_device_train_batch_size`: 16
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- `per_device_eval_batch_size`: 16
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- `gradient_accumulation_steps`: 8
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- `
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- `
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- `warmup_ratio`: 0.1
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- `push_to_hub`: True
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- `hub_model_id`: CocoRoF/ModernBERT-SimCSE-
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- `hub_strategy`: checkpoint
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- `batch_sampler`: no_duplicates
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- `gradient_accumulation_steps`: 8
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- `eval_accumulation_steps`: None
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- `torch_empty_cache_steps`: None
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- `learning_rate`:
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- `weight_decay`: 0.0
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- `adam_beta1`: 0.9
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- `adam_beta2`: 0.999
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- `adam_epsilon`: 1e-08
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- `max_grad_norm`: 1.0
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-
- `num_train_epochs`:
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- `max_steps`: -1
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- `lr_scheduler_type`: linear
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- `lr_scheduler_kwargs`: {}
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-
- `warmup_ratio`: 0.
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- `warmup_steps`: 0
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- `log_level`: passive
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- `log_level_replica`: warning
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- `use_legacy_prediction_loop`: False
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- `push_to_hub`: True
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- `resume_from_checkpoint`: None
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-
- `hub_model_id`: CocoRoF/ModernBERT-SimCSE-
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- `hub_strategy`: checkpoint
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- `hub_private_repo`: None
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- `hub_always_push`: False
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</details>
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### Training Logs
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| Epoch | Step | Training Loss | Validation Loss | sts_dev_spearman_max |
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|:------:|:----:|:-------------:|:---------------:|:--------------------:|
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|
| 450 |
|
|
|
|
| 451 |
|
| 452 |
### Framework Versions
|
| 453 |
- Python: 3.11.10
|
|
|
|
| 4 |
- sentence-similarity
|
| 5 |
- feature-extraction
|
| 6 |
- generated_from_trainer
|
| 7 |
+
- dataset_size:449904
|
| 8 |
- loss:CosineSimilarityLoss
|
| 9 |
base_model: CocoRoF/ModernBERT-SimCSE_v04
|
| 10 |
widget:
|
|
|
|
| 34 |
- 우리와 같은 태양계가 은하계 밖에서 존재할 수도 있을 것입니다.
|
| 35 |
- 그 여자는 데이트하러 가는 중이다.
|
| 36 |
- 녹색 버스가 도로를 따라 내려간다.
|
| 37 |
+
datasets:
|
| 38 |
+
- x2bee/misc_sts_pairs_v2_kor_kosimcse
|
| 39 |
pipeline_tag: sentence-similarity
|
| 40 |
library_name: sentence-transformers
|
| 41 |
metrics:
|
|
|
|
| 60 |
type: sts_dev
|
| 61 |
metrics:
|
| 62 |
- type: pearson_cosine
|
| 63 |
+
value: 0.7947107267431892
|
| 64 |
name: Pearson Cosine
|
| 65 |
- type: spearman_cosine
|
| 66 |
+
value: 0.8008029938863944
|
| 67 |
name: Spearman Cosine
|
| 68 |
- type: pearson_euclidean
|
| 69 |
+
value: 0.7729649224022854
|
| 70 |
name: Pearson Euclidean
|
| 71 |
- type: spearman_euclidean
|
| 72 |
+
value: 0.7731836226956725
|
| 73 |
name: Spearman Euclidean
|
| 74 |
- type: pearson_manhattan
|
| 75 |
+
value: 0.7728910393964163
|
| 76 |
name: Pearson Manhattan
|
| 77 |
- type: spearman_manhattan
|
| 78 |
+
value: 0.7732333197709114
|
| 79 |
name: Spearman Manhattan
|
| 80 |
- type: pearson_dot
|
| 81 |
+
value: 0.6023258275823691
|
| 82 |
name: Pearson Dot
|
| 83 |
- type: spearman_dot
|
| 84 |
+
value: 0.5958009787049323
|
| 85 |
name: Spearman Dot
|
| 86 |
- type: pearson_max
|
| 87 |
+
value: 0.7947107267431892
|
| 88 |
name: Pearson Max
|
| 89 |
- type: spearman_max
|
| 90 |
+
value: 0.8008029938863944
|
| 91 |
name: Spearman Max
|
| 92 |
---
|
| 93 |
|
| 94 |
# SentenceTransformer based on CocoRoF/ModernBERT-SimCSE_v04
|
| 95 |
|
| 96 |
+
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [CocoRoF/ModernBERT-SimCSE_v04](https://huggingface.co/CocoRoF/ModernBERT-SimCSE_v04) on the [misc_sts_pairs_v2_kor_kosimcse](https://huggingface.co/datasets/x2bee/misc_sts_pairs_v2_kor_kosimcse) dataset. It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
|
| 97 |
|
| 98 |
## Model Details
|
| 99 |
|
|
|
|
| 103 |
- **Maximum Sequence Length:** 512 tokens
|
| 104 |
- **Output Dimensionality:** 768 dimensions
|
| 105 |
- **Similarity Function:** Cosine Similarity
|
| 106 |
+
- **Training Dataset:**
|
| 107 |
+
- [misc_sts_pairs_v2_kor_kosimcse](https://huggingface.co/datasets/x2bee/misc_sts_pairs_v2_kor_kosimcse)
|
| 108 |
<!-- - **Language:** Unknown -->
|
| 109 |
<!-- - **License:** Unknown -->
|
| 110 |
|
|
|
|
| 139 |
from sentence_transformers import SentenceTransformer
|
| 140 |
|
| 141 |
# Download from the 🤗 Hub
|
| 142 |
+
model = SentenceTransformer("CocoRoF/ModernBERT-SimCSE-multitask_v05")
|
| 143 |
# Run inference
|
| 144 |
sentences = [
|
| 145 |
'버스가 바쁜 길을 따라 운전한다.',
|
|
|
|
| 191 |
|
| 192 |
| Metric | Value |
|
| 193 |
|:-------------------|:-----------|
|
| 194 |
+
| pearson_cosine | 0.7947 |
|
| 195 |
+
| spearman_cosine | 0.8008 |
|
| 196 |
+
| pearson_euclidean | 0.773 |
|
| 197 |
+
| spearman_euclidean | 0.7732 |
|
| 198 |
+
| pearson_manhattan | 0.7729 |
|
| 199 |
+
| spearman_manhattan | 0.7732 |
|
| 200 |
+
| pearson_dot | 0.6023 |
|
| 201 |
+
| spearman_dot | 0.5958 |
|
| 202 |
+
| pearson_max | 0.7947 |
|
| 203 |
+
| **spearman_max** | **0.8008** |
|
| 204 |
|
| 205 |
<!--
|
| 206 |
## Bias, Risks and Limitations
|
|
|
|
| 218 |
|
| 219 |
### Training Dataset
|
| 220 |
|
| 221 |
+
#### misc_sts_pairs_v2_kor_kosimcse
|
|
|
|
| 222 |
|
| 223 |
+
* Dataset: [misc_sts_pairs_v2_kor_kosimcse](https://huggingface.co/datasets/x2bee/misc_sts_pairs_v2_kor_kosimcse) at [e747415](https://huggingface.co/datasets/x2bee/misc_sts_pairs_v2_kor_kosimcse/tree/e747415cfe9ff51d1c1550b8a07e5014c01dea59)
|
| 224 |
+
* Size: 449,904 training samples
|
| 225 |
* Columns: <code>sentence1</code>, <code>sentence2</code>, and <code>score</code>
|
| 226 |
* Approximate statistics based on the first 1000 samples:
|
| 227 |
+
| | sentence1 | sentence2 | score |
|
| 228 |
+
|:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------|
|
| 229 |
+
| type | string | string | float |
|
| 230 |
+
| details | <ul><li>min: 6 tokens</li><li>mean: 15.81 tokens</li><li>max: 66 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 16.18 tokens</li><li>max: 48 tokens</li></ul> | <ul><li>min: 0.11</li><li>mean: 0.77</li><li>max: 1.0</li></ul> |
|
| 231 |
* Samples:
|
| 232 |
+
| sentence1 | sentence2 | score |
|
| 233 |
+
|:-------------------------------------------------|:-------------------------------------------|:--------------------------------|
|
| 234 |
+
| <code>주홍글씨는 언제 출판되었습니까?</code> | <code>《주홍글씨》는 몇 년에 출판되었습니까?</code> | <code>0.8638778924942017</code> |
|
| 235 |
+
| <code>폴란드에서 빨간색과 흰색은 무엇을 의미합니까?</code> | <code>폴란드 국기의 색상은 무엇입니까?</code> | <code>0.6773715019226074</code> |
|
| 236 |
+
| <code>노르만인들은 방어를 위해 모트와 베일리 성을 어떻게 사용했는가?</code> | <code>11세기에는 어떻게 모트와 베일리 성을 만들었습니까?</code> | <code>0.7460665702819824</code> |
|
| 237 |
* Loss: [<code>CosineSimilarityLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cosinesimilarityloss) with these parameters:
|
| 238 |
```json
|
| 239 |
{
|
|
|
|
| 274 |
- `per_device_train_batch_size`: 16
|
| 275 |
- `per_device_eval_batch_size`: 16
|
| 276 |
- `gradient_accumulation_steps`: 8
|
| 277 |
+
- `num_train_epochs`: 2.0
|
| 278 |
+
- `warmup_ratio`: 0.2
|
|
|
|
| 279 |
- `push_to_hub`: True
|
| 280 |
+
- `hub_model_id`: CocoRoF/ModernBERT-SimCSE-multitask_v05
|
| 281 |
- `hub_strategy`: checkpoint
|
| 282 |
- `batch_sampler`: no_duplicates
|
| 283 |
|
|
|
|
| 295 |
- `gradient_accumulation_steps`: 8
|
| 296 |
- `eval_accumulation_steps`: None
|
| 297 |
- `torch_empty_cache_steps`: None
|
| 298 |
+
- `learning_rate`: 5e-05
|
| 299 |
- `weight_decay`: 0.0
|
| 300 |
- `adam_beta1`: 0.9
|
| 301 |
- `adam_beta2`: 0.999
|
| 302 |
- `adam_epsilon`: 1e-08
|
| 303 |
- `max_grad_norm`: 1.0
|
| 304 |
+
- `num_train_epochs`: 2.0
|
| 305 |
- `max_steps`: -1
|
| 306 |
- `lr_scheduler_type`: linear
|
| 307 |
- `lr_scheduler_kwargs`: {}
|
| 308 |
+
- `warmup_ratio`: 0.2
|
| 309 |
- `warmup_steps`: 0
|
| 310 |
- `log_level`: passive
|
| 311 |
- `log_level_replica`: warning
|
|
|
|
| 364 |
- `use_legacy_prediction_loop`: False
|
| 365 |
- `push_to_hub`: True
|
| 366 |
- `resume_from_checkpoint`: None
|
| 367 |
+
- `hub_model_id`: CocoRoF/ModernBERT-SimCSE-multitask_v05
|
| 368 |
- `hub_strategy`: checkpoint
|
| 369 |
- `hub_private_repo`: None
|
| 370 |
- `hub_always_push`: False
|
|
|
|
| 403 |
</details>
|
| 404 |
|
| 405 |
### Training Logs
|
| 406 |
+
<details><summary>Click to expand</summary>
|
| 407 |
+
|
| 408 |
| Epoch | Step | Training Loss | Validation Loss | sts_dev_spearman_max |
|
| 409 |
|:------:|:----:|:-------------:|:---------------:|:--------------------:|
|
| 410 |
+
| 0.0028 | 10 | 0.0202 | - | - |
|
| 411 |
+
| 0.0057 | 20 | 0.0184 | - | - |
|
| 412 |
+
| 0.0085 | 30 | 0.018 | - | - |
|
| 413 |
+
| 0.0114 | 40 | 0.0173 | - | - |
|
| 414 |
+
| 0.0142 | 50 | 0.0193 | - | - |
|
| 415 |
+
| 0.0171 | 60 | 0.0158 | - | - |
|
| 416 |
+
| 0.0199 | 70 | 0.016 | - | - |
|
| 417 |
+
| 0.0228 | 80 | 0.0139 | - | - |
|
| 418 |
+
| 0.0256 | 90 | 0.0143 | - | - |
|
| 419 |
+
| 0.0285 | 100 | 0.0138 | - | - |
|
| 420 |
+
| 0.0313 | 110 | 0.0127 | - | - |
|
| 421 |
+
| 0.0341 | 120 | 0.0115 | - | - |
|
| 422 |
+
| 0.0370 | 130 | 0.0117 | - | - |
|
| 423 |
+
| 0.0398 | 140 | 0.0111 | - | - |
|
| 424 |
+
| 0.0427 | 150 | 0.0111 | - | - |
|
| 425 |
+
| 0.0455 | 160 | 0.0106 | - | - |
|
| 426 |
+
| 0.0484 | 170 | 0.01 | - | - |
|
| 427 |
+
| 0.0512 | 180 | 0.0103 | - | - |
|
| 428 |
+
| 0.0541 | 190 | 0.0106 | - | - |
|
| 429 |
+
| 0.0569 | 200 | 0.0102 | - | - |
|
| 430 |
+
| 0.0597 | 210 | 0.0103 | - | - |
|
| 431 |
+
| 0.0626 | 220 | 0.0109 | - | - |
|
| 432 |
+
| 0.0654 | 230 | 0.0099 | - | - |
|
| 433 |
+
| 0.0683 | 240 | 0.0086 | - | - |
|
| 434 |
+
| 0.0711 | 250 | 0.01 | 0.0448 | 0.7642 |
|
| 435 |
+
| 0.0740 | 260 | 0.0098 | - | - |
|
| 436 |
+
| 0.0768 | 270 | 0.0094 | - | - |
|
| 437 |
+
| 0.0797 | 280 | 0.0097 | - | - |
|
| 438 |
+
| 0.0825 | 290 | 0.0094 | - | - |
|
| 439 |
+
| 0.0854 | 300 | 0.0095 | - | - |
|
| 440 |
+
| 0.0882 | 310 | 0.0098 | - | - |
|
| 441 |
+
| 0.0910 | 320 | 0.0092 | - | - |
|
| 442 |
+
| 0.0939 | 330 | 0.0095 | - | - |
|
| 443 |
+
| 0.0967 | 340 | 0.0103 | - | - |
|
| 444 |
+
| 0.0996 | 350 | 0.0097 | - | - |
|
| 445 |
+
| 0.1024 | 360 | 0.0091 | - | - |
|
| 446 |
+
| 0.1053 | 370 | 0.0094 | - | - |
|
| 447 |
+
| 0.1081 | 380 | 0.0088 | - | - |
|
| 448 |
+
| 0.1110 | 390 | 0.009 | - | - |
|
| 449 |
+
| 0.1138 | 400 | 0.0098 | - | - |
|
| 450 |
+
| 0.1166 | 410 | 0.0083 | - | - |
|
| 451 |
+
| 0.1195 | 420 | 0.0099 | - | - |
|
| 452 |
+
| 0.1223 | 430 | 0.0094 | - | - |
|
| 453 |
+
| 0.1252 | 440 | 0.0092 | - | - |
|
| 454 |
+
| 0.1280 | 450 | 0.009 | - | - |
|
| 455 |
+
| 0.1309 | 460 | 0.0088 | - | - |
|
| 456 |
+
| 0.1337 | 470 | 0.0092 | - | - |
|
| 457 |
+
| 0.1366 | 480 | 0.0083 | - | - |
|
| 458 |
+
| 0.1394 | 490 | 0.0089 | - | - |
|
| 459 |
+
| 0.1423 | 500 | 0.0089 | 0.0444 | 0.7725 |
|
| 460 |
+
| 0.1451 | 510 | 0.0095 | - | - |
|
| 461 |
+
| 0.1479 | 520 | 0.0095 | - | - |
|
| 462 |
+
| 0.1508 | 530 | 0.0091 | - | - |
|
| 463 |
+
| 0.1536 | 540 | 0.0082 | - | - |
|
| 464 |
+
| 0.1565 | 550 | 0.0091 | - | - |
|
| 465 |
+
| 0.1593 | 560 | 0.0086 | - | - |
|
| 466 |
+
| 0.1622 | 570 | 0.009 | - | - |
|
| 467 |
+
| 0.1650 | 580 | 0.0088 | - | - |
|
| 468 |
+
| 0.1679 | 590 | 0.0087 | - | - |
|
| 469 |
+
| 0.1707 | 600 | 0.0089 | - | - |
|
| 470 |
+
| 0.1735 | 610 | 0.009 | - | - |
|
| 471 |
+
| 0.1764 | 620 | 0.0088 | - | - |
|
| 472 |
+
| 0.1792 | 630 | 0.0088 | - | - |
|
| 473 |
+
| 0.1821 | 640 | 0.0081 | - | - |
|
| 474 |
+
| 0.1849 | 650 | 0.0082 | - | - |
|
| 475 |
+
| 0.1878 | 660 | 0.0088 | - | - |
|
| 476 |
+
| 0.1906 | 670 | 0.0086 | - | - |
|
| 477 |
+
| 0.1935 | 680 | 0.0085 | - | - |
|
| 478 |
+
| 0.1963 | 690 | 0.009 | - | - |
|
| 479 |
+
| 0.1992 | 700 | 0.0083 | - | - |
|
| 480 |
+
| 0.2020 | 710 | 0.0088 | - | - |
|
| 481 |
+
| 0.2048 | 720 | 0.0088 | - | - |
|
| 482 |
+
| 0.2077 | 730 | 0.0087 | - | - |
|
| 483 |
+
| 0.2105 | 740 | 0.0088 | - | - |
|
| 484 |
+
| 0.2134 | 750 | 0.008 | 0.0465 | 0.7798 |
|
| 485 |
+
| 0.2162 | 760 | 0.0087 | - | - |
|
| 486 |
+
| 0.2191 | 770 | 0.0087 | - | - |
|
| 487 |
+
| 0.2219 | 780 | 0.009 | - | - |
|
| 488 |
+
| 0.2248 | 790 | 0.0085 | - | - |
|
| 489 |
+
| 0.2276 | 800 | 0.009 | - | - |
|
| 490 |
+
| 0.2304 | 810 | 0.0082 | - | - |
|
| 491 |
+
| 0.2333 | 820 | 0.0073 | - | - |
|
| 492 |
+
| 0.2361 | 830 | 0.0078 | - | - |
|
| 493 |
+
| 0.2390 | 840 | 0.0088 | - | - |
|
| 494 |
+
| 0.2418 | 850 | 0.0077 | - | - |
|
| 495 |
+
| 0.2447 | 860 | 0.008 | - | - |
|
| 496 |
+
| 0.2475 | 870 | 0.008 | - | - |
|
| 497 |
+
| 0.2504 | 880 | 0.0086 | - | - |
|
| 498 |
+
| 0.2532 | 890 | 0.0083 | - | - |
|
| 499 |
+
| 0.2561 | 900 | 0.0081 | - | - |
|
| 500 |
+
| 0.2589 | 910 | 0.0081 | - | - |
|
| 501 |
+
| 0.2617 | 920 | 0.0077 | - | - |
|
| 502 |
+
| 0.2646 | 930 | 0.0083 | - | - |
|
| 503 |
+
| 0.2674 | 940 | 0.0081 | - | - |
|
| 504 |
+
| 0.2703 | 950 | 0.0069 | - | - |
|
| 505 |
+
| 0.2731 | 960 | 0.0084 | - | - |
|
| 506 |
+
| 0.2760 | 970 | 0.0075 | - | - |
|
| 507 |
+
| 0.2788 | 980 | 0.0081 | - | - |
|
| 508 |
+
| 0.2817 | 990 | 0.0086 | - | - |
|
| 509 |
+
| 0.2845 | 1000 | 0.0079 | 0.0473 | 0.7855 |
|
| 510 |
+
| 0.2874 | 1010 | 0.0088 | - | - |
|
| 511 |
+
| 0.2902 | 1020 | 0.0073 | - | - |
|
| 512 |
+
| 0.2930 | 1030 | 0.008 | - | - |
|
| 513 |
+
| 0.2959 | 1040 | 0.0073 | - | - |
|
| 514 |
+
| 0.2987 | 1050 | 0.008 | - | - |
|
| 515 |
+
| 0.3016 | 1060 | 0.0074 | - | - |
|
| 516 |
+
| 0.3044 | 1070 | 0.007 | - | - |
|
| 517 |
+
| 0.3073 | 1080 | 0.0075 | - | - |
|
| 518 |
+
| 0.3101 | 1090 | 0.0077 | - | - |
|
| 519 |
+
| 0.3130 | 1100 | 0.0076 | - | - |
|
| 520 |
+
| 0.3158 | 1110 | 0.0082 | - | - |
|
| 521 |
+
| 0.3186 | 1120 | 0.0073 | - | - |
|
| 522 |
+
| 0.3215 | 1130 | 0.007 | - | - |
|
| 523 |
+
| 0.3243 | 1140 | 0.0077 | - | - |
|
| 524 |
+
| 0.3272 | 1150 | 0.0074 | - | - |
|
| 525 |
+
| 0.3300 | 1160 | 0.0076 | - | - |
|
| 526 |
+
| 0.3329 | 1170 | 0.0078 | - | - |
|
| 527 |
+
| 0.3357 | 1180 | 0.0073 | - | - |
|
| 528 |
+
| 0.3386 | 1190 | 0.0077 | - | - |
|
| 529 |
+
| 0.3414 | 1200 | 0.0068 | - | - |
|
| 530 |
+
| 0.3443 | 1210 | 0.0079 | - | - |
|
| 531 |
+
| 0.3471 | 1220 | 0.0073 | - | - |
|
| 532 |
+
| 0.3499 | 1230 | 0.0075 | - | - |
|
| 533 |
+
| 0.3528 | 1240 | 0.0078 | - | - |
|
| 534 |
+
| 0.3556 | 1250 | 0.0073 | 0.0472 | 0.7855 |
|
| 535 |
+
| 0.3585 | 1260 | 0.0073 | - | - |
|
| 536 |
+
| 0.3613 | 1270 | 0.007 | - | - |
|
| 537 |
+
| 0.3642 | 1280 | 0.0068 | - | - |
|
| 538 |
+
| 0.3670 | 1290 | 0.0067 | - | - |
|
| 539 |
+
| 0.3699 | 1300 | 0.0078 | - | - |
|
| 540 |
+
| 0.3727 | 1310 | 0.0072 | - | - |
|
| 541 |
+
| 0.3755 | 1320 | 0.0071 | - | - |
|
| 542 |
+
| 0.3784 | 1330 | 0.0068 | - | - |
|
| 543 |
+
| 0.3812 | 1340 | 0.0068 | - | - |
|
| 544 |
+
| 0.3841 | 1350 | 0.0074 | - | - |
|
| 545 |
+
| 0.3869 | 1360 | 0.0074 | - | - |
|
| 546 |
+
| 0.3898 | 1370 | 0.0077 | - | - |
|
| 547 |
+
| 0.3926 | 1380 | 0.0069 | - | - |
|
| 548 |
+
| 0.3955 | 1390 | 0.0079 | - | - |
|
| 549 |
+
| 0.3983 | 1400 | 0.0066 | - | - |
|
| 550 |
+
| 0.4012 | 1410 | 0.008 | - | - |
|
| 551 |
+
| 0.4040 | 1420 | 0.008 | - | - |
|
| 552 |
+
| 0.4068 | 1430 | 0.0071 | - | - |
|
| 553 |
+
| 0.4097 | 1440 | 0.0066 | - | - |
|
| 554 |
+
| 0.4125 | 1450 | 0.0079 | - | - |
|
| 555 |
+
| 0.4154 | 1460 | 0.0075 | - | - |
|
| 556 |
+
| 0.4182 | 1470 | 0.0066 | - | - |
|
| 557 |
+
| 0.4211 | 1480 | 0.007 | - | - |
|
| 558 |
+
| 0.4239 | 1490 | 0.0066 | - | - |
|
| 559 |
+
| 0.4268 | 1500 | 0.0066 | 0.0474 | 0.7908 |
|
| 560 |
+
| 0.4296 | 1510 | 0.0075 | - | - |
|
| 561 |
+
| 0.4324 | 1520 | 0.0072 | - | - |
|
| 562 |
+
| 0.4353 | 1530 | 0.0072 | - | - |
|
| 563 |
+
| 0.4381 | 1540 | 0.0067 | - | - |
|
| 564 |
+
| 0.4410 | 1550 | 0.0073 | - | - |
|
| 565 |
+
| 0.4438 | 1560 | 0.0066 | - | - |
|
| 566 |
+
| 0.4467 | 1570 | 0.0063 | - | - |
|
| 567 |
+
| 0.4495 | 1580 | 0.0074 | - | - |
|
| 568 |
+
| 0.4524 | 1590 | 0.0075 | - | - |
|
| 569 |
+
| 0.4552 | 1600 | 0.0069 | - | - |
|
| 570 |
+
| 0.4581 | 1610 | 0.0065 | - | - |
|
| 571 |
+
| 0.4609 | 1620 | 0.007 | - | - |
|
| 572 |
+
| 0.4637 | 1630 | 0.0067 | - | - |
|
| 573 |
+
| 0.4666 | 1640 | 0.0067 | - | - |
|
| 574 |
+
| 0.4694 | 1650 | 0.0072 | - | - |
|
| 575 |
+
| 0.4723 | 1660 | 0.007 | - | - |
|
| 576 |
+
| 0.4751 | 1670 | 0.0078 | - | - |
|
| 577 |
+
| 0.4780 | 1680 | 0.0069 | - | - |
|
| 578 |
+
| 0.4808 | 1690 | 0.0067 | - | - |
|
| 579 |
+
| 0.4837 | 1700 | 0.0072 | - | - |
|
| 580 |
+
| 0.4865 | 1710 | 0.0071 | - | - |
|
| 581 |
+
| 0.4893 | 1720 | 0.0069 | - | - |
|
| 582 |
+
| 0.4922 | 1730 | 0.0074 | - | - |
|
| 583 |
+
| 0.4950 | 1740 | 0.0073 | - | - |
|
| 584 |
+
| 0.4979 | 1750 | 0.0064 | 0.0499 | 0.7938 |
|
| 585 |
+
| 0.5007 | 1760 | 0.0064 | - | - |
|
| 586 |
+
| 0.5036 | 1770 | 0.0068 | - | - |
|
| 587 |
+
| 0.5064 | 1780 | 0.007 | - | - |
|
| 588 |
+
| 0.5093 | 1790 | 0.0065 | - | - |
|
| 589 |
+
| 0.5121 | 1800 | 0.0073 | - | - |
|
| 590 |
+
| 0.5150 | 1810 | 0.0061 | - | - |
|
| 591 |
+
| 0.5178 | 1820 | 0.0071 | - | - |
|
| 592 |
+
| 0.5206 | 1830 | 0.0058 | - | - |
|
| 593 |
+
| 0.5235 | 1840 | 0.0065 | - | - |
|
| 594 |
+
| 0.5263 | 1850 | 0.0067 | - | - |
|
| 595 |
+
| 0.5292 | 1860 | 0.0063 | - | - |
|
| 596 |
+
| 0.5320 | 1870 | 0.007 | - | - |
|
| 597 |
+
| 0.5349 | 1880 | 0.0069 | - | - |
|
| 598 |
+
| 0.5377 | 1890 | 0.0073 | - | - |
|
| 599 |
+
| 0.5406 | 1900 | 0.0067 | - | - |
|
| 600 |
+
| 0.5434 | 1910 | 0.0068 | - | - |
|
| 601 |
+
| 0.5462 | 1920 | 0.0066 | - | - |
|
| 602 |
+
| 0.5491 | 1930 | 0.007 | - | - |
|
| 603 |
+
| 0.5519 | 1940 | 0.006 | - | - |
|
| 604 |
+
| 0.5548 | 1950 | 0.0062 | - | - |
|
| 605 |
+
| 0.5576 | 1960 | 0.0062 | - | - |
|
| 606 |
+
| 0.5605 | 1970 | 0.0067 | - | - |
|
| 607 |
+
| 0.5633 | 1980 | 0.0063 | - | - |
|
| 608 |
+
| 0.5662 | 1990 | 0.006 | - | - |
|
| 609 |
+
| 0.5690 | 2000 | 0.0067 | 0.0478 | 0.7943 |
|
| 610 |
+
| 0.5719 | 2010 | 0.0076 | - | - |
|
| 611 |
+
| 0.5747 | 2020 | 0.0069 | - | - |
|
| 612 |
+
| 0.5775 | 2030 | 0.0065 | - | - |
|
| 613 |
+
| 0.5804 | 2040 | 0.007 | - | - |
|
| 614 |
+
| 0.5832 | 2050 | 0.006 | - | - |
|
| 615 |
+
| 0.5861 | 2060 | 0.0064 | - | - |
|
| 616 |
+
| 0.5889 | 2070 | 0.0063 | - | - |
|
| 617 |
+
| 0.5918 | 2080 | 0.0067 | - | - |
|
| 618 |
+
| 0.5946 | 2090 | 0.0064 | - | - |
|
| 619 |
+
| 0.5975 | 2100 | 0.0062 | - | - |
|
| 620 |
+
| 0.6003 | 2110 | 0.0063 | - | - |
|
| 621 |
+
| 0.6032 | 2120 | 0.0063 | - | - |
|
| 622 |
+
| 0.6060 | 2130 | 0.0074 | - | - |
|
| 623 |
+
| 0.6088 | 2140 | 0.0067 | - | - |
|
| 624 |
+
| 0.6117 | 2150 | 0.006 | - | - |
|
| 625 |
+
| 0.6145 | 2160 | 0.0062 | - | - |
|
| 626 |
+
| 0.6174 | 2170 | 0.007 | - | - |
|
| 627 |
+
| 0.6202 | 2180 | 0.0069 | - | - |
|
| 628 |
+
| 0.6231 | 2190 | 0.007 | - | - |
|
| 629 |
+
| 0.6259 | 2200 | 0.0065 | - | - |
|
| 630 |
+
| 0.6288 | 2210 | 0.0071 | - | - |
|
| 631 |
+
| 0.6316 | 2220 | 0.007 | - | - |
|
| 632 |
+
| 0.6344 | 2230 | 0.0064 | - | - |
|
| 633 |
+
| 0.6373 | 2240 | 0.0061 | - | - |
|
| 634 |
+
| 0.6401 | 2250 | 0.0062 | 0.0464 | 0.7935 |
|
| 635 |
+
| 0.6430 | 2260 | 0.0069 | - | - |
|
| 636 |
+
| 0.6458 | 2270 | 0.0062 | - | - |
|
| 637 |
+
| 0.6487 | 2280 | 0.0063 | - | - |
|
| 638 |
+
| 0.6515 | 2290 | 0.0063 | - | - |
|
| 639 |
+
| 0.6544 | 2300 | 0.006 | - | - |
|
| 640 |
+
| 0.6572 | 2310 | 0.0064 | - | - |
|
| 641 |
+
| 0.6601 | 2320 | 0.0061 | - | - |
|
| 642 |
+
| 0.6629 | 2330 | 0.0065 | - | - |
|
| 643 |
+
| 0.6657 | 2340 | 0.0061 | - | - |
|
| 644 |
+
| 0.6686 | 2350 | 0.0067 | - | - |
|
| 645 |
+
| 0.6714 | 2360 | 0.0066 | - | - |
|
| 646 |
+
| 0.6743 | 2370 | 0.0068 | - | - |
|
| 647 |
+
| 0.6771 | 2380 | 0.0071 | - | - |
|
| 648 |
+
| 0.6800 | 2390 | 0.0064 | - | - |
|
| 649 |
+
| 0.6828 | 2400 | 0.0064 | - | - |
|
| 650 |
+
| 0.6857 | 2410 | 0.0064 | - | - |
|
| 651 |
+
| 0.6885 | 2420 | 0.0064 | - | - |
|
| 652 |
+
| 0.6913 | 2430 | 0.0062 | - | - |
|
| 653 |
+
| 0.6942 | 2440 | 0.0067 | - | - |
|
| 654 |
+
| 0.6970 | 2450 | 0.0062 | - | - |
|
| 655 |
+
| 0.6999 | 2460 | 0.0059 | - | - |
|
| 656 |
+
| 0.7027 | 2470 | 0.0063 | - | - |
|
| 657 |
+
| 0.7056 | 2480 | 0.0055 | - | - |
|
| 658 |
+
| 0.7084 | 2490 | 0.0074 | - | - |
|
| 659 |
+
| 0.7113 | 2500 | 0.0064 | 0.0488 | 0.7939 |
|
| 660 |
+
| 0.7141 | 2510 | 0.006 | - | - |
|
| 661 |
+
| 0.7170 | 2520 | 0.0061 | - | - |
|
| 662 |
+
| 0.7198 | 2530 | 0.0064 | - | - |
|
| 663 |
+
| 0.7226 | 2540 | 0.0059 | - | - |
|
| 664 |
+
| 0.7255 | 2550 | 0.0064 | - | - |
|
| 665 |
+
| 0.7283 | 2560 | 0.0061 | - | - |
|
| 666 |
+
| 0.7312 | 2570 | 0.0062 | - | - |
|
| 667 |
+
| 0.7340 | 2580 | 0.0068 | - | - |
|
| 668 |
+
| 0.7369 | 2590 | 0.0061 | - | - |
|
| 669 |
+
| 0.7397 | 2600 | 0.0065 | - | - |
|
| 670 |
+
| 0.7426 | 2610 | 0.0055 | - | - |
|
| 671 |
+
| 0.7454 | 2620 | 0.0057 | - | - |
|
| 672 |
+
| 0.7482 | 2630 | 0.0064 | - | - |
|
| 673 |
+
| 0.7511 | 2640 | 0.0056 | - | - |
|
| 674 |
+
| 0.7539 | 2650 | 0.0059 | - | - |
|
| 675 |
+
| 0.7568 | 2660 | 0.0059 | - | - |
|
| 676 |
+
| 0.7596 | 2670 | 0.0064 | - | - |
|
| 677 |
+
| 0.7625 | 2680 | 0.0067 | - | - |
|
| 678 |
+
| 0.7653 | 2690 | 0.0062 | - | - |
|
| 679 |
+
| 0.7682 | 2700 | 0.0056 | - | - |
|
| 680 |
+
| 0.7710 | 2710 | 0.0063 | - | - |
|
| 681 |
+
| 0.7739 | 2720 | 0.0064 | - | - |
|
| 682 |
+
| 0.7767 | 2730 | 0.0063 | - | - |
|
| 683 |
+
| 0.7795 | 2740 | 0.0062 | - | - |
|
| 684 |
+
| 0.7824 | 2750 | 0.0058 | 0.0479 | 0.7987 |
|
| 685 |
+
| 0.7852 | 2760 | 0.0063 | - | - |
|
| 686 |
+
| 0.7881 | 2770 | 0.0061 | - | - |
|
| 687 |
+
| 0.7909 | 2780 | 0.0059 | - | - |
|
| 688 |
+
| 0.7938 | 2790 | 0.0061 | - | - |
|
| 689 |
+
| 0.7966 | 2800 | 0.0059 | - | - |
|
| 690 |
+
| 0.7995 | 2810 | 0.0058 | - | - |
|
| 691 |
+
| 0.8023 | 2820 | 0.0057 | - | - |
|
| 692 |
+
| 0.8051 | 2830 | 0.0059 | - | - |
|
| 693 |
+
| 0.8080 | 2840 | 0.0058 | - | - |
|
| 694 |
+
| 0.8108 | 2850 | 0.0068 | - | - |
|
| 695 |
+
| 0.8137 | 2860 | 0.006 | - | - |
|
| 696 |
+
| 0.8165 | 2870 | 0.0058 | - | - |
|
| 697 |
+
| 0.8194 | 2880 | 0.0061 | - | - |
|
| 698 |
+
| 0.8222 | 2890 | 0.0058 | - | - |
|
| 699 |
+
| 0.8251 | 2900 | 0.0055 | - | - |
|
| 700 |
+
| 0.8279 | 2910 | 0.006 | - | - |
|
| 701 |
+
| 0.8308 | 2920 | 0.0063 | - | - |
|
| 702 |
+
| 0.8336 | 2930 | 0.0066 | - | - |
|
| 703 |
+
| 0.8364 | 2940 | 0.0059 | - | - |
|
| 704 |
+
| 0.8393 | 2950 | 0.0056 | - | - |
|
| 705 |
+
| 0.8421 | 2960 | 0.006 | - | - |
|
| 706 |
+
| 0.8450 | 2970 | 0.0058 | - | - |
|
| 707 |
+
| 0.8478 | 2980 | 0.006 | - | - |
|
| 708 |
+
| 0.8507 | 2990 | 0.0056 | - | - |
|
| 709 |
+
| 0.8535 | 3000 | 0.0062 | 0.0511 | 0.7996 |
|
| 710 |
+
| 0.8564 | 3010 | 0.0059 | - | - |
|
| 711 |
+
| 0.8592 | 3020 | 0.0064 | - | - |
|
| 712 |
+
| 0.8621 | 3030 | 0.0064 | - | - |
|
| 713 |
+
| 0.8649 | 3040 | 0.006 | - | - |
|
| 714 |
+
| 0.8677 | 3050 | 0.0059 | - | - |
|
| 715 |
+
| 0.8706 | 3060 | 0.0055 | - | - |
|
| 716 |
+
| 0.8734 | 3070 | 0.0056 | - | - |
|
| 717 |
+
| 0.8763 | 3080 | 0.0058 | - | - |
|
| 718 |
+
| 0.8791 | 3090 | 0.0057 | - | - |
|
| 719 |
+
| 0.8820 | 3100 | 0.0058 | - | - |
|
| 720 |
+
| 0.8848 | 3110 | 0.0062 | - | - |
|
| 721 |
+
| 0.8877 | 3120 | 0.0058 | - | - |
|
| 722 |
+
| 0.8905 | 3130 | 0.0058 | - | - |
|
| 723 |
+
| 0.8933 | 3140 | 0.0055 | - | - |
|
| 724 |
+
| 0.8962 | 3150 | 0.0056 | - | - |
|
| 725 |
+
| 0.8990 | 3160 | 0.0055 | - | - |
|
| 726 |
+
| 0.9019 | 3170 | 0.0054 | - | - |
|
| 727 |
+
| 0.9047 | 3180 | 0.0059 | - | - |
|
| 728 |
+
| 0.9076 | 3190 | 0.0056 | - | - |
|
| 729 |
+
| 0.9104 | 3200 | 0.0057 | - | - |
|
| 730 |
+
| 0.9133 | 3210 | 0.0055 | - | - |
|
| 731 |
+
| 0.9161 | 3220 | 0.0061 | - | - |
|
| 732 |
+
| 0.9190 | 3230 | 0.0055 | - | - |
|
| 733 |
+
| 0.9218 | 3240 | 0.0062 | - | - |
|
| 734 |
+
| 0.9246 | 3250 | 0.006 | 0.0508 | 0.7989 |
|
| 735 |
+
| 0.9275 | 3260 | 0.0058 | - | - |
|
| 736 |
+
| 0.9303 | 3270 | 0.0053 | - | - |
|
| 737 |
+
| 0.9332 | 3280 | 0.0064 | - | - |
|
| 738 |
+
| 0.9360 | 3290 | 0.006 | - | - |
|
| 739 |
+
| 0.9389 | 3300 | 0.0057 | - | - |
|
| 740 |
+
| 0.9417 | 3310 | 0.0059 | - | - |
|
| 741 |
+
| 0.9446 | 3320 | 0.0057 | - | - |
|
| 742 |
+
| 0.9474 | 3330 | 0.0056 | - | - |
|
| 743 |
+
| 0.9502 | 3340 | 0.0056 | - | - |
|
| 744 |
+
| 0.9531 | 3350 | 0.0061 | - | - |
|
| 745 |
+
| 0.9559 | 3360 | 0.0053 | - | - |
|
| 746 |
+
| 0.9588 | 3370 | 0.0056 | - | - |
|
| 747 |
+
| 0.9616 | 3380 | 0.006 | - | - |
|
| 748 |
+
| 0.9645 | 3390 | 0.0066 | - | - |
|
| 749 |
+
| 0.9673 | 3400 | 0.0062 | - | - |
|
| 750 |
+
| 0.9702 | 3410 | 0.0053 | - | - |
|
| 751 |
+
| 0.9730 | 3420 | 0.0062 | - | - |
|
| 752 |
+
| 0.9759 | 3430 | 0.0057 | - | - |
|
| 753 |
+
| 0.9787 | 3440 | 0.0059 | - | - |
|
| 754 |
+
| 0.9815 | 3450 | 0.0061 | - | - |
|
| 755 |
+
| 0.9844 | 3460 | 0.0057 | - | - |
|
| 756 |
+
| 0.9872 | 3470 | 0.0054 | - | - |
|
| 757 |
+
| 0.9901 | 3480 | 0.0054 | - | - |
|
| 758 |
+
| 0.9929 | 3490 | 0.0057 | - | - |
|
| 759 |
+
| 0.9958 | 3500 | 0.0056 | 0.0485 | 0.7958 |
|
| 760 |
+
| 0.9986 | 3510 | 0.0053 | - | - |
|
| 761 |
+
| 1.0014 | 3520 | 0.0054 | - | - |
|
| 762 |
+
| 1.0043 | 3530 | 0.0056 | - | - |
|
| 763 |
+
| 1.0071 | 3540 | 0.0055 | - | - |
|
| 764 |
+
| 1.0100 | 3550 | 0.0055 | - | - |
|
| 765 |
+
| 1.0128 | 3560 | 0.0056 | - | - |
|
| 766 |
+
| 1.0156 | 3570 | 0.0058 | - | - |
|
| 767 |
+
| 1.0185 | 3580 | 0.0055 | - | - |
|
| 768 |
+
| 1.0213 | 3590 | 0.0058 | - | - |
|
| 769 |
+
| 1.0242 | 3600 | 0.0058 | - | - |
|
| 770 |
+
| 1.0270 | 3610 | 0.0061 | - | - |
|
| 771 |
+
| 1.0299 | 3620 | 0.006 | - | - |
|
| 772 |
+
| 1.0327 | 3630 | 0.0057 | - | - |
|
| 773 |
+
| 1.0356 | 3640 | 0.0054 | - | - |
|
| 774 |
+
| 1.0384 | 3650 | 0.0059 | - | - |
|
| 775 |
+
| 1.0413 | 3660 | 0.0057 | - | - |
|
| 776 |
+
| 1.0441 | 3670 | 0.0057 | - | - |
|
| 777 |
+
| 1.0469 | 3680 | 0.0057 | - | - |
|
| 778 |
+
| 1.0498 | 3690 | 0.0055 | - | - |
|
| 779 |
+
| 1.0526 | 3700 | 0.0057 | - | - |
|
| 780 |
+
| 1.0555 | 3710 | 0.0057 | - | - |
|
| 781 |
+
| 1.0583 | 3720 | 0.0056 | - | - |
|
| 782 |
+
| 1.0612 | 3730 | 0.0057 | - | - |
|
| 783 |
+
| 1.0640 | 3740 | 0.005 | - | - |
|
| 784 |
+
| 1.0669 | 3750 | 0.0051 | 0.0525 | 0.7979 |
|
| 785 |
+
| 1.0697 | 3760 | 0.0052 | - | - |
|
| 786 |
+
| 1.0725 | 3770 | 0.0055 | - | - |
|
| 787 |
+
| 1.0754 | 3780 | 0.005 | - | - |
|
| 788 |
+
| 1.0782 | 3790 | 0.0056 | - | - |
|
| 789 |
+
| 1.0811 | 3800 | 0.0054 | - | - |
|
| 790 |
+
| 1.0839 | 3810 | 0.0054 | - | - |
|
| 791 |
+
| 1.0868 | 3820 | 0.0058 | - | - |
|
| 792 |
+
| 1.0896 | 3830 | 0.0049 | - | - |
|
| 793 |
+
| 1.0925 | 3840 | 0.0053 | - | - |
|
| 794 |
+
| 1.0953 | 3850 | 0.0055 | - | - |
|
| 795 |
+
| 1.0982 | 3860 | 0.0057 | - | - |
|
| 796 |
+
| 1.1010 | 3870 | 0.0059 | - | - |
|
| 797 |
+
| 1.1038 | 3880 | 0.0049 | - | - |
|
| 798 |
+
| 1.1067 | 3890 | 0.0051 | - | - |
|
| 799 |
+
| 1.1095 | 3900 | 0.0051 | - | - |
|
| 800 |
+
| 1.1124 | 3910 | 0.0054 | - | - |
|
| 801 |
+
| 1.1152 | 3920 | 0.0051 | - | - |
|
| 802 |
+
| 1.1181 | 3930 | 0.0052 | - | - |
|
| 803 |
+
| 1.1209 | 3940 | 0.0051 | - | - |
|
| 804 |
+
| 1.1238 | 3950 | 0.0055 | - | - |
|
| 805 |
+
| 1.1266 | 3960 | 0.0052 | - | - |
|
| 806 |
+
| 1.1294 | 3970 | 0.0049 | - | - |
|
| 807 |
+
| 1.1323 | 3980 | 0.0054 | - | - |
|
| 808 |
+
| 1.1351 | 3990 | 0.0053 | - | - |
|
| 809 |
+
| 1.1380 | 4000 | 0.0046 | 0.0475 | 0.8005 |
|
| 810 |
+
| 1.1408 | 4010 | 0.0049 | - | - |
|
| 811 |
+
| 1.1437 | 4020 | 0.0054 | - | - |
|
| 812 |
+
| 1.1465 | 4030 | 0.0054 | - | - |
|
| 813 |
+
| 1.1494 | 4040 | 0.0051 | - | - |
|
| 814 |
+
| 1.1522 | 4050 | 0.0052 | - | - |
|
| 815 |
+
| 1.1551 | 4060 | 0.0052 | - | - |
|
| 816 |
+
| 1.1579 | 4070 | 0.0049 | - | - |
|
| 817 |
+
| 1.1607 | 4080 | 0.005 | - | - |
|
| 818 |
+
| 1.1636 | 4090 | 0.0054 | - | - |
|
| 819 |
+
| 1.1664 | 4100 | 0.0049 | - | - |
|
| 820 |
+
| 1.1693 | 4110 | 0.0054 | - | - |
|
| 821 |
+
| 1.1721 | 4120 | 0.0051 | - | - |
|
| 822 |
+
| 1.1750 | 4130 | 0.0048 | - | - |
|
| 823 |
+
| 1.1778 | 4140 | 0.0053 | - | - |
|
| 824 |
+
| 1.1807 | 4150 | 0.0051 | - | - |
|
| 825 |
+
| 1.1835 | 4160 | 0.0045 | - | - |
|
| 826 |
+
| 1.1864 | 4170 | 0.0057 | - | - |
|
| 827 |
+
| 1.1892 | 4180 | 0.0051 | - | - |
|
| 828 |
+
| 1.1920 | 4190 | 0.0051 | - | - |
|
| 829 |
+
| 1.1949 | 4200 | 0.0052 | - | - |
|
| 830 |
+
| 1.1977 | 4210 | 0.0054 | - | - |
|
| 831 |
+
| 1.2006 | 4220 | 0.005 | - | - |
|
| 832 |
+
| 1.2034 | 4230 | 0.0046 | - | - |
|
| 833 |
+
| 1.2063 | 4240 | 0.0051 | - | - |
|
| 834 |
+
| 1.2091 | 4250 | 0.0053 | 0.0470 | 0.7988 |
|
| 835 |
+
| 1.2120 | 4260 | 0.0051 | - | - |
|
| 836 |
+
| 1.2148 | 4270 | 0.0049 | - | - |
|
| 837 |
+
| 1.2176 | 4280 | 0.0047 | - | - |
|
| 838 |
+
| 1.2205 | 4290 | 0.0051 | - | - |
|
| 839 |
+
| 1.2233 | 4300 | 0.0047 | - | - |
|
| 840 |
+
| 1.2262 | 4310 | 0.005 | - | - |
|
| 841 |
+
| 1.2290 | 4320 | 0.0051 | - | - |
|
| 842 |
+
| 1.2319 | 4330 | 0.0051 | - | - |
|
| 843 |
+
| 1.2347 | 4340 | 0.0046 | - | - |
|
| 844 |
+
| 1.2376 | 4350 | 0.0052 | - | - |
|
| 845 |
+
| 1.2404 | 4360 | 0.0044 | - | - |
|
| 846 |
+
| 1.2433 | 4370 | 0.0049 | - | - |
|
| 847 |
+
| 1.2461 | 4380 | 0.0051 | - | - |
|
| 848 |
+
| 1.2489 | 4390 | 0.0052 | - | - |
|
| 849 |
+
| 1.2518 | 4400 | 0.0049 | - | - |
|
| 850 |
+
| 1.2546 | 4410 | 0.0051 | - | - |
|
| 851 |
+
| 1.2575 | 4420 | 0.005 | - | - |
|
| 852 |
+
| 1.2603 | 4430 | 0.0045 | - | - |
|
| 853 |
+
| 1.2632 | 4440 | 0.005 | - | - |
|
| 854 |
+
| 1.2660 | 4450 | 0.005 | - | - |
|
| 855 |
+
| 1.2689 | 4460 | 0.0044 | - | - |
|
| 856 |
+
| 1.2717 | 4470 | 0.0051 | - | - |
|
| 857 |
+
| 1.2745 | 4480 | 0.005 | - | - |
|
| 858 |
+
| 1.2774 | 4490 | 0.0045 | - | - |
|
| 859 |
+
| 1.2802 | 4500 | 0.0051 | 0.0550 | 0.8063 |
|
| 860 |
+
| 1.2831 | 4510 | 0.0048 | - | - |
|
| 861 |
+
| 1.2859 | 4520 | 0.0053 | - | - |
|
| 862 |
+
| 1.2888 | 4530 | 0.0045 | - | - |
|
| 863 |
+
| 1.2916 | 4540 | 0.0045 | - | - |
|
| 864 |
+
| 1.2945 | 4550 | 0.0046 | - | - |
|
| 865 |
+
| 1.2973 | 4560 | 0.0047 | - | - |
|
| 866 |
+
| 1.3002 | 4570 | 0.0049 | - | - |
|
| 867 |
+
| 1.3030 | 4580 | 0.0045 | - | - |
|
| 868 |
+
| 1.3058 | 4590 | 0.0046 | - | - |
|
| 869 |
+
| 1.3087 | 4600 | 0.0051 | - | - |
|
| 870 |
+
| 1.3115 | 4610 | 0.0048 | - | - |
|
| 871 |
+
| 1.3144 | 4620 | 0.0045 | - | - |
|
| 872 |
+
| 1.3172 | 4630 | 0.0051 | - | - |
|
| 873 |
+
| 1.3201 | 4640 | 0.0045 | - | - |
|
| 874 |
+
| 1.3229 | 4650 | 0.0047 | - | - |
|
| 875 |
+
| 1.3258 | 4660 | 0.0048 | - | - |
|
| 876 |
+
| 1.3286 | 4670 | 0.0044 | - | - |
|
| 877 |
+
| 1.3314 | 4680 | 0.0043 | - | - |
|
| 878 |
+
| 1.3343 | 4690 | 0.0048 | - | - |
|
| 879 |
+
| 1.3371 | 4700 | 0.0046 | - | - |
|
| 880 |
+
| 1.3400 | 4710 | 0.0042 | - | - |
|
| 881 |
+
| 1.3428 | 4720 | 0.0043 | - | - |
|
| 882 |
+
| 1.3457 | 4730 | 0.0048 | - | - |
|
| 883 |
+
| 1.3485 | 4740 | 0.005 | - | - |
|
| 884 |
+
| 1.3514 | 4750 | 0.0044 | 0.0447 | 0.8075 |
|
| 885 |
+
| 1.3542 | 4760 | 0.0045 | - | - |
|
| 886 |
+
| 1.3571 | 4770 | 0.0046 | - | - |
|
| 887 |
+
| 1.3599 | 4780 | 0.0045 | - | - |
|
| 888 |
+
| 1.3627 | 4790 | 0.0044 | - | - |
|
| 889 |
+
| 1.3656 | 4800 | 0.004 | - | - |
|
| 890 |
+
| 1.3684 | 4810 | 0.0044 | - | - |
|
| 891 |
+
| 1.3713 | 4820 | 0.0045 | - | - |
|
| 892 |
+
| 1.3741 | 4830 | 0.0041 | - | - |
|
| 893 |
+
| 1.3770 | 4840 | 0.0043 | - | - |
|
| 894 |
+
| 1.3798 | 4850 | 0.0042 | - | - |
|
| 895 |
+
| 1.3827 | 4860 | 0.0044 | - | - |
|
| 896 |
+
| 1.3855 | 4870 | 0.0047 | - | - |
|
| 897 |
+
| 1.3883 | 4880 | 0.0041 | - | - |
|
| 898 |
+
| 1.3912 | 4890 | 0.0045 | - | - |
|
| 899 |
+
| 1.3940 | 4900 | 0.0047 | - | - |
|
| 900 |
+
| 1.3969 | 4910 | 0.0042 | - | - |
|
| 901 |
+
| 1.3997 | 4920 | 0.0047 | - | - |
|
| 902 |
+
| 1.4026 | 4930 | 0.0045 | - | - |
|
| 903 |
+
| 1.4054 | 4940 | 0.0048 | - | - |
|
| 904 |
+
| 1.4083 | 4950 | 0.0042 | - | - |
|
| 905 |
+
| 1.4111 | 4960 | 0.0043 | - | - |
|
| 906 |
+
| 1.4140 | 4970 | 0.0046 | - | - |
|
| 907 |
+
| 1.4168 | 4980 | 0.0046 | - | - |
|
| 908 |
+
| 1.4196 | 4990 | 0.0041 | - | - |
|
| 909 |
+
| 1.4225 | 5000 | 0.0044 | 0.0551 | 0.8041 |
|
| 910 |
+
| 1.4253 | 5010 | 0.0043 | - | - |
|
| 911 |
+
| 1.4282 | 5020 | 0.0045 | - | - |
|
| 912 |
+
| 1.4310 | 5030 | 0.0047 | - | - |
|
| 913 |
+
| 1.4339 | 5040 | 0.0046 | - | - |
|
| 914 |
+
| 1.4367 | 5050 | 0.0048 | - | - |
|
| 915 |
+
| 1.4396 | 5060 | 0.0046 | - | - |
|
| 916 |
+
| 1.4424 | 5070 | 0.0044 | - | - |
|
| 917 |
+
| 1.4453 | 5080 | 0.0039 | - | - |
|
| 918 |
+
| 1.4481 | 5090 | 0.0042 | - | - |
|
| 919 |
+
| 1.4509 | 5100 | 0.0044 | - | - |
|
| 920 |
+
| 1.4538 | 5110 | 0.0043 | - | - |
|
| 921 |
+
| 1.4566 | 5120 | 0.0043 | - | - |
|
| 922 |
+
| 1.4595 | 5130 | 0.0042 | - | - |
|
| 923 |
+
| 1.4623 | 5140 | 0.0046 | - | - |
|
| 924 |
+
| 1.4652 | 5150 | 0.0043 | - | - |
|
| 925 |
+
| 1.4680 | 5160 | 0.0043 | - | - |
|
| 926 |
+
| 1.4709 | 5170 | 0.0046 | - | - |
|
| 927 |
+
| 1.4737 | 5180 | 0.0045 | - | - |
|
| 928 |
+
| 1.4765 | 5190 | 0.0045 | - | - |
|
| 929 |
+
| 1.4794 | 5200 | 0.0041 | - | - |
|
| 930 |
+
| 1.4822 | 5210 | 0.0044 | - | - |
|
| 931 |
+
| 1.4851 | 5220 | 0.0045 | - | - |
|
| 932 |
+
| 1.4879 | 5230 | 0.0043 | - | - |
|
| 933 |
+
| 1.4908 | 5240 | 0.0043 | - | - |
|
| 934 |
+
| 1.4936 | 5250 | 0.0047 | 0.0529 | 0.8067 |
|
| 935 |
+
| 1.4965 | 5260 | 0.0042 | - | - |
|
| 936 |
+
| 1.4993 | 5270 | 0.0042 | - | - |
|
| 937 |
+
| 1.5022 | 5280 | 0.004 | - | - |
|
| 938 |
+
| 1.5050 | 5290 | 0.0042 | - | - |
|
| 939 |
+
| 1.5078 | 5300 | 0.004 | - | - |
|
| 940 |
+
| 1.5107 | 5310 | 0.004 | - | - |
|
| 941 |
+
| 1.5135 | 5320 | 0.004 | - | - |
|
| 942 |
+
| 1.5164 | 5330 | 0.0043 | - | - |
|
| 943 |
+
| 1.5192 | 5340 | 0.004 | - | - |
|
| 944 |
+
| 1.5221 | 5350 | 0.0041 | - | - |
|
| 945 |
+
| 1.5249 | 5360 | 0.0041 | - | - |
|
| 946 |
+
| 1.5278 | 5370 | 0.004 | - | - |
|
| 947 |
+
| 1.5306 | 5380 | 0.004 | - | - |
|
| 948 |
+
| 1.5334 | 5390 | 0.0042 | - | - |
|
| 949 |
+
| 1.5363 | 5400 | 0.0043 | - | - |
|
| 950 |
+
| 1.5391 | 5410 | 0.0044 | - | - |
|
| 951 |
+
| 1.5420 | 5420 | 0.0043 | - | - |
|
| 952 |
+
| 1.5448 | 5430 | 0.004 | - | - |
|
| 953 |
+
| 1.5477 | 5440 | 0.0043 | - | - |
|
| 954 |
+
| 1.5505 | 5450 | 0.0039 | - | - |
|
| 955 |
+
| 1.5534 | 5460 | 0.004 | - | - |
|
| 956 |
+
| 1.5562 | 5470 | 0.0038 | - | - |
|
| 957 |
+
| 1.5591 | 5480 | 0.0041 | - | - |
|
| 958 |
+
| 1.5619 | 5490 | 0.0043 | - | - |
|
| 959 |
+
| 1.5647 | 5500 | 0.0038 | 0.0489 | 0.8012 |
|
| 960 |
+
| 1.5676 | 5510 | 0.0037 | - | - |
|
| 961 |
+
| 1.5704 | 5520 | 0.0047 | - | - |
|
| 962 |
+
| 1.5733 | 5530 | 0.004 | - | - |
|
| 963 |
+
| 1.5761 | 5540 | 0.0043 | - | - |
|
| 964 |
+
| 1.5790 | 5550 | 0.0039 | - | - |
|
| 965 |
+
| 1.5818 | 5560 | 0.004 | - | - |
|
| 966 |
+
| 1.5847 | 5570 | 0.0039 | - | - |
|
| 967 |
+
| 1.5875 | 5580 | 0.0038 | - | - |
|
| 968 |
+
| 1.5903 | 5590 | 0.0042 | - | - |
|
| 969 |
+
| 1.5932 | 5600 | 0.004 | - | - |
|
| 970 |
+
| 1.5960 | 5610 | 0.0042 | - | - |
|
| 971 |
+
| 1.5989 | 5620 | 0.0039 | - | - |
|
| 972 |
+
| 1.6017 | 5630 | 0.0041 | - | - |
|
| 973 |
+
| 1.6046 | 5640 | 0.004 | - | - |
|
| 974 |
+
| 1.6074 | 5650 | 0.0042 | - | - |
|
| 975 |
+
| 1.6103 | 5660 | 0.004 | - | - |
|
| 976 |
+
| 1.6131 | 5670 | 0.0037 | - | - |
|
| 977 |
+
| 1.6160 | 5680 | 0.0041 | - | - |
|
| 978 |
+
| 1.6188 | 5690 | 0.0041 | - | - |
|
| 979 |
+
| 1.6216 | 5700 | 0.0039 | - | - |
|
| 980 |
+
| 1.6245 | 5710 | 0.0042 | - | - |
|
| 981 |
+
| 1.6273 | 5720 | 0.0038 | - | - |
|
| 982 |
+
| 1.6302 | 5730 | 0.0042 | - | - |
|
| 983 |
+
| 1.6330 | 5740 | 0.0037 | - | - |
|
| 984 |
+
| 1.6359 | 5750 | 0.0037 | 0.0494 | 0.7999 |
|
| 985 |
+
| 1.6387 | 5760 | 0.0037 | - | - |
|
| 986 |
+
| 1.6416 | 5770 | 0.0038 | - | - |
|
| 987 |
+
| 1.6444 | 5780 | 0.0038 | - | - |
|
| 988 |
+
| 1.6472 | 5790 | 0.0038 | - | - |
|
| 989 |
+
| 1.6501 | 5800 | 0.004 | - | - |
|
| 990 |
+
| 1.6529 | 5810 | 0.0038 | - | - |
|
| 991 |
+
| 1.6558 | 5820 | 0.004 | - | - |
|
| 992 |
+
| 1.6586 | 5830 | 0.0039 | - | - |
|
| 993 |
+
| 1.6615 | 5840 | 0.0036 | - | - |
|
| 994 |
+
| 1.6643 | 5850 | 0.0038 | - | - |
|
| 995 |
+
| 1.6672 | 5860 | 0.0036 | - | - |
|
| 996 |
+
| 1.6700 | 5870 | 0.004 | - | - |
|
| 997 |
+
| 1.6729 | 5880 | 0.004 | - | - |
|
| 998 |
+
| 1.6757 | 5890 | 0.004 | - | - |
|
| 999 |
+
| 1.6785 | 5900 | 0.0041 | - | - |
|
| 1000 |
+
| 1.6814 | 5910 | 0.0037 | - | - |
|
| 1001 |
+
| 1.6842 | 5920 | 0.0036 | - | - |
|
| 1002 |
+
| 1.6871 | 5930 | 0.0037 | - | - |
|
| 1003 |
+
| 1.6899 | 5940 | 0.0037 | - | - |
|
| 1004 |
+
| 1.6928 | 5950 | 0.0036 | - | - |
|
| 1005 |
+
| 1.6956 | 5960 | 0.0038 | - | - |
|
| 1006 |
+
| 1.6985 | 5970 | 0.0034 | - | - |
|
| 1007 |
+
| 1.7013 | 5980 | 0.0035 | - | - |
|
| 1008 |
+
| 1.7042 | 5990 | 0.0036 | - | - |
|
| 1009 |
+
| 1.7070 | 6000 | 0.004 | 0.0525 | 0.8026 |
|
| 1010 |
+
| 1.7098 | 6010 | 0.0041 | - | - |
|
| 1011 |
+
| 1.7127 | 6020 | 0.0036 | - | - |
|
| 1012 |
+
| 1.7155 | 6030 | 0.004 | - | - |
|
| 1013 |
+
| 1.7184 | 6040 | 0.0039 | - | - |
|
| 1014 |
+
| 1.7212 | 6050 | 0.0036 | - | - |
|
| 1015 |
+
| 1.7241 | 6060 | 0.0038 | - | - |
|
| 1016 |
+
| 1.7269 | 6070 | 0.004 | - | - |
|
| 1017 |
+
| 1.7298 | 6080 | 0.0036 | - | - |
|
| 1018 |
+
| 1.7326 | 6090 | 0.0037 | - | - |
|
| 1019 |
+
| 1.7354 | 6100 | 0.0039 | - | - |
|
| 1020 |
+
| 1.7383 | 6110 | 0.0036 | - | - |
|
| 1021 |
+
| 1.7411 | 6120 | 0.0036 | - | - |
|
| 1022 |
+
| 1.7440 | 6130 | 0.0034 | - | - |
|
| 1023 |
+
| 1.7468 | 6140 | 0.0038 | - | - |
|
| 1024 |
+
| 1.7497 | 6150 | 0.0036 | - | - |
|
| 1025 |
+
| 1.7525 | 6160 | 0.0035 | - | - |
|
| 1026 |
+
| 1.7554 | 6170 | 0.0035 | - | - |
|
| 1027 |
+
| 1.7582 | 6180 | 0.0038 | - | - |
|
| 1028 |
+
| 1.7611 | 6190 | 0.0038 | - | - |
|
| 1029 |
+
| 1.7639 | 6200 | 0.0038 | - | - |
|
| 1030 |
+
| 1.7667 | 6210 | 0.0032 | - | - |
|
| 1031 |
+
| 1.7696 | 6220 | 0.0036 | - | - |
|
| 1032 |
+
| 1.7724 | 6230 | 0.0037 | - | - |
|
| 1033 |
+
| 1.7753 | 6240 | 0.0038 | - | - |
|
| 1034 |
+
| 1.7781 | 6250 | 0.0037 | 0.0515 | 0.7994 |
|
| 1035 |
+
| 1.7810 | 6260 | 0.0036 | - | - |
|
| 1036 |
+
| 1.7838 | 6270 | 0.0035 | - | - |
|
| 1037 |
+
| 1.7867 | 6280 | 0.0039 | - | - |
|
| 1038 |
+
| 1.7895 | 6290 | 0.0037 | - | - |
|
| 1039 |
+
| 1.7923 | 6300 | 0.0036 | - | - |
|
| 1040 |
+
| 1.7952 | 6310 | 0.0036 | - | - |
|
| 1041 |
+
| 1.7980 | 6320 | 0.0037 | - | - |
|
| 1042 |
+
| 1.8009 | 6330 | 0.0033 | - | - |
|
| 1043 |
+
| 1.8037 | 6340 | 0.0033 | - | - |
|
| 1044 |
+
| 1.8066 | 6350 | 0.0035 | - | - |
|
| 1045 |
+
| 1.8094 | 6360 | 0.0034 | - | - |
|
| 1046 |
+
| 1.8123 | 6370 | 0.0038 | - | - |
|
| 1047 |
+
| 1.8151 | 6380 | 0.0035 | - | - |
|
| 1048 |
+
| 1.8180 | 6390 | 0.0035 | - | - |
|
| 1049 |
+
| 1.8208 | 6400 | 0.0036 | - | - |
|
| 1050 |
+
| 1.8236 | 6410 | 0.0034 | - | - |
|
| 1051 |
+
| 1.8265 | 6420 | 0.0033 | - | - |
|
| 1052 |
+
| 1.8293 | 6430 | 0.0038 | - | - |
|
| 1053 |
+
| 1.8322 | 6440 | 0.0036 | - | - |
|
| 1054 |
+
| 1.8350 | 6450 | 0.0037 | - | - |
|
| 1055 |
+
| 1.8379 | 6460 | 0.0034 | - | - |
|
| 1056 |
+
| 1.8407 | 6470 | 0.0034 | - | - |
|
| 1057 |
+
| 1.8436 | 6480 | 0.0036 | - | - |
|
| 1058 |
+
| 1.8464 | 6490 | 0.0037 | - | - |
|
| 1059 |
+
| 1.8492 | 6500 | 0.0031 | 0.0532 | 0.8034 |
|
| 1060 |
+
| 1.8521 | 6510 | 0.0035 | - | - |
|
| 1061 |
+
| 1.8549 | 6520 | 0.0036 | - | - |
|
| 1062 |
+
| 1.8578 | 6530 | 0.0037 | - | - |
|
| 1063 |
+
| 1.8606 | 6540 | 0.0038 | - | - |
|
| 1064 |
+
| 1.8635 | 6550 | 0.0035 | - | - |
|
| 1065 |
+
| 1.8663 | 6560 | 0.0037 | - | - |
|
| 1066 |
+
| 1.8692 | 6570 | 0.0032 | - | - |
|
| 1067 |
+
| 1.8720 | 6580 | 0.0037 | - | - |
|
| 1068 |
+
| 1.8749 | 6590 | 0.0034 | - | - |
|
| 1069 |
+
| 1.8777 | 6600 | 0.0032 | - | - |
|
| 1070 |
+
| 1.8805 | 6610 | 0.0033 | - | - |
|
| 1071 |
+
| 1.8834 | 6620 | 0.0035 | - | - |
|
| 1072 |
+
| 1.8862 | 6630 | 0.0034 | - | - |
|
| 1073 |
+
| 1.8891 | 6640 | 0.0032 | - | - |
|
| 1074 |
+
| 1.8919 | 6650 | 0.0036 | - | - |
|
| 1075 |
+
| 1.8948 | 6660 | 0.0032 | - | - |
|
| 1076 |
+
| 1.8976 | 6670 | 0.0032 | - | - |
|
| 1077 |
+
| 1.9005 | 6680 | 0.003 | - | - |
|
| 1078 |
+
| 1.9033 | 6690 | 0.0032 | - | - |
|
| 1079 |
+
| 1.9061 | 6700 | 0.0034 | - | - |
|
| 1080 |
+
| 1.9090 | 6710 | 0.0034 | - | - |
|
| 1081 |
+
| 1.9118 | 6720 | 0.0032 | - | - |
|
| 1082 |
+
| 1.9147 | 6730 | 0.0036 | - | - |
|
| 1083 |
+
| 1.9175 | 6740 | 0.0036 | - | - |
|
| 1084 |
+
| 1.9204 | 6750 | 0.0034 | 0.0494 | 0.8002 |
|
| 1085 |
+
| 1.9232 | 6760 | 0.0036 | - | - |
|
| 1086 |
+
| 1.9261 | 6770 | 0.0034 | - | - |
|
| 1087 |
+
| 1.9289 | 6780 | 0.0032 | - | - |
|
| 1088 |
+
| 1.9318 | 6790 | 0.0032 | - | - |
|
| 1089 |
+
| 1.9346 | 6800 | 0.0036 | - | - |
|
| 1090 |
+
| 1.9374 | 6810 | 0.0032 | - | - |
|
| 1091 |
+
| 1.9403 | 6820 | 0.0033 | - | - |
|
| 1092 |
+
| 1.9431 | 6830 | 0.0031 | - | - |
|
| 1093 |
+
| 1.9460 | 6840 | 0.0034 | - | - |
|
| 1094 |
+
| 1.9488 | 6850 | 0.0033 | - | - |
|
| 1095 |
+
| 1.9517 | 6860 | 0.0033 | - | - |
|
| 1096 |
+
| 1.9545 | 6870 | 0.003 | - | - |
|
| 1097 |
+
| 1.9574 | 6880 | 0.0031 | - | - |
|
| 1098 |
+
| 1.9602 | 6890 | 0.0035 | - | - |
|
| 1099 |
+
| 1.9630 | 6900 | 0.0033 | - | - |
|
| 1100 |
+
| 1.9659 | 6910 | 0.0034 | - | - |
|
| 1101 |
+
| 1.9687 | 6920 | 0.0033 | - | - |
|
| 1102 |
+
| 1.9716 | 6930 | 0.003 | - | - |
|
| 1103 |
+
| 1.9744 | 6940 | 0.0034 | - | - |
|
| 1104 |
+
| 1.9773 | 6950 | 0.0032 | - | - |
|
| 1105 |
+
| 1.9801 | 6960 | 0.0031 | - | - |
|
| 1106 |
+
| 1.9830 | 6970 | 0.0033 | - | - |
|
| 1107 |
+
| 1.9858 | 6980 | 0.0032 | - | - |
|
| 1108 |
+
| 1.9887 | 6990 | 0.0031 | - | - |
|
| 1109 |
+
| 1.9915 | 7000 | 0.0033 | 0.0492 | 0.8008 |
|
| 1110 |
+
| 1.9943 | 7010 | 0.0033 | - | - |
|
| 1111 |
+
| 1.9972 | 7020 | 0.0031 | - | - |
|
| 1112 |
|
| 1113 |
+
</details>
|
| 1114 |
|
| 1115 |
### Framework Versions
|
| 1116 |
- Python: 3.11.10
|
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
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|
| 3 |
size 610640632
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
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|
| 3 |
size 610640632
|