- replaced OpenAIGPTAdam with OpenAIAdam in docs
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README.md
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README.md
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@ -126,7 +126,7 @@ This package comprises the following classes that can be imported in Python and
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- `BertAdam` - Bert version of Adam algorithm with weight decay fix, warmup and linear decay of the learning rate.
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- Optimizer for **OpenAI GPT** (in the [`optimization_openai.py`](./pytorch_pretrained_bert/optimization_openai.py) file):
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- `OpenAIGPTAdam` - OpenAI GPT version of Adam algorithm with weight decay fix, warmup and linear decay of the learning rate.
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- `OpenAIAdam` - OpenAI GPT version of Adam algorithm with weight decay fix, warmup and linear decay of the learning rate.
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- Configuration classes for BERT, OpenAI GPT and Transformer-XL (in the respective [`modeling.py`](./pytorch_pretrained_bert/modeling.py), [`modeling_openai.py`](./pytorch_pretrained_bert/modeling_openai.py), [`modeling_transfo_xl.py`](./pytorch_pretrained_bert/modeling_transfo_xl.py) files):
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- `BertConfig` - Configuration class to store the configuration of a `BertModel` with utilities to read and write from JSON configuration files.
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@ -994,12 +994,12 @@ The optimizer accepts the following arguments:
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- `weight_decay:` Weight decay. Default : `0.01`
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- `max_grad_norm` : Maximum norm for the gradients (`-1` means no clipping). Default : `1.0`
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#### `OpenAIGPTAdam`
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#### `OpenAIAdam`
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`OpenAIGPTAdam` is similar to `BertAdam`.
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The differences with `BertAdam` is that `OpenAIGPTAdam` compensate for bias as in the regular Adam optimizer.
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`OpenAIAdam` is similar to `BertAdam`.
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The differences with `BertAdam` is that `OpenAIAdam` compensate for bias as in the regular Adam optimizer.
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`OpenAIGPTAdam` accepts the same arguments as `BertAdam`.
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`OpenAIAdam` accepts the same arguments as `BertAdam`.
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#### Learning Rate Schedules
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The `.optimization` module also provides additional schedules in the form of schedule objects that inherit from `_LRSchedule`.
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